lr: 1e-05
sub_26:Test (Best Model) - Loss: 0.8188 - Accuracy: 0.5507 - F1: 0.5088
sub_6:Test (Best Model) - Loss: 1.0349 - Accuracy: 0.5588 - F1: 0.5029
sub_2:Test (Best Model) - Loss: 0.8492 - Accuracy: 0.6377 - F1: 0.6021
sub_24:Test (Best Model) - Loss: 0.9395 - Accuracy: 0.5294 - F1: 0.4613
sub_14:Test (Best Model) - Loss: 1.1555 - Accuracy: 0.5147 - F1: 0.4591
sub_4:Test (Best Model) - Loss: 0.8466 - Accuracy: 0.6522 - F1: 0.6013
sub_16:Test (Best Model) - Loss: 0.9642 - Accuracy: 0.6324 - F1: 0.5912
sub_20:Test (Best Model) - Loss: 0.7665 - Accuracy: 0.5882 - F1: 0.5101
sub_1:Test (Best Model) - Loss: 0.9056 - Accuracy: 0.5147 - F1: 0.5233
sub_10:Test (Best Model) - Loss: 1.1039 - Accuracy: 0.3971 - F1: 0.3296
sub_8:Test (Best Model) - Loss: 1.5193 - Accuracy: 0.5147 - F1: 0.4979
sub_15:Test (Best Model) - Loss: 1.0040 - Accuracy: 0.4412 - F1: 0.3524
sub_11:Test (Best Model) - Loss: 0.8193 - Accuracy: 0.6232 - F1: 0.5933
sub_12:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.6471 - F1: 0.6379
sub_29:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.6324 - F1: 0.6331
sub_7:Test (Best Model) - Loss: 0.8539 - Accuracy: 0.5588 - F1: 0.5201
sub_25:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.9275 - F1: 0.9293
sub_23:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.6957 - F1: 0.6952
sub_21:Test (Best Model) - Loss: 0.5270 - Accuracy: 0.9412 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6912 - F1: 0.6671
sub_19:Test (Best Model) - Loss: 1.6326 - Accuracy: 0.3676 - F1: 0.3160
sub_18:Test (Best Model) - Loss: 0.8630 - Accuracy: 0.5942 - F1: 0.5497
sub_26:Test (Best Model) - Loss: 0.9218 - Accuracy: 0.6087 - F1: 0.6258
sub_6:Test (Best Model) - Loss: 0.9821 - Accuracy: 0.5000 - F1: 0.4602
sub_13:Test (Best Model) - Loss: 1.2627 - Accuracy: 0.4265 - F1: 0.3328
sub_22:Test (Best Model) - Loss: 1.3000 - Accuracy: 0.3676 - F1: 0.3762
sub_2:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.8116 - F1: 0.8029
sub_17:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6667 - F1: 0.6096
sub_28:Test (Best Model) - Loss: 1.2338 - Accuracy: 0.3382 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 1.2850 - Accuracy: 0.4559 - F1: 0.3857
sub_16:Test (Best Model) - Loss: 0.9103 - Accuracy: 0.6912 - F1: 0.6800
sub_27:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6667 - F1: 0.6096
sub_4:Test (Best Model) - Loss: 0.9015 - Accuracy: 0.6377 - F1: 0.5848
sub_24:Test (Best Model) - Loss: 1.1894 - Accuracy: 0.4559 - F1: 0.3553
sub_10:Test (Best Model) - Loss: 0.9723 - Accuracy: 0.5147 - F1: 0.5238
sub_9:Test (Best Model) - Loss: 0.8588 - Accuracy: 0.7500 - F1: 0.7579
sub_12:Test (Best Model) - Loss: 0.8585 - Accuracy: 0.6176 - F1: 0.6007
sub_8:Test (Best Model) - Loss: 0.8631 - Accuracy: 0.7059 - F1: 0.6237
sub_14:Test (Best Model) - Loss: 1.4177 - Accuracy: 0.4706 - F1: 0.3824
sub_29:Test (Best Model) - Loss: 0.9916 - Accuracy: 0.4706 - F1: 0.5119
sub_18:Test (Best Model) - Loss: 1.0341 - Accuracy: 0.4348 - F1: 0.3771
sub_20:Test (Best Model) - Loss: 0.8022 - Accuracy: 0.7500 - F1: 0.6961
sub_21:Test (Best Model) - Loss: 0.9302 - Accuracy: 0.6765 - F1: 0.6886
sub_17:Test (Best Model) - Loss: 0.7595 - Accuracy: 0.7391 - F1: 0.7466
sub_1:Test (Best Model) - Loss: 0.9799 - Accuracy: 0.5735 - F1: 0.5563
sub_27:Test (Best Model) - Loss: 0.7595 - Accuracy: 0.7391 - F1: 0.7466
sub_11:Test (Best Model) - Loss: 0.7961 - Accuracy: 0.7101 - F1: 0.6928
sub_25:Test (Best Model) - Loss: 0.4910 - Accuracy: 0.9275 - F1: 0.9277
sub_22:Test (Best Model) - Loss: 1.1943 - Accuracy: 0.4118 - F1: 0.4030
sub_2:Test (Best Model) - Loss: 0.7500 - Accuracy: 0.7101 - F1: 0.6741
sub_7:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.7794 - F1: 0.7377
sub_15:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.6324 - F1: 0.6275
sub_26:Test (Best Model) - Loss: 0.8826 - Accuracy: 0.5362 - F1: 0.4691
sub_3:Test (Best Model) - Loss: 0.8657 - Accuracy: 0.7794 - F1: 0.7754
sub_24:Test (Best Model) - Loss: 0.8409 - Accuracy: 0.6912 - F1: 0.6783
sub_5:Test (Best Model) - Loss: 1.2974 - Accuracy: 0.5735 - F1: 0.5352
sub_6:Test (Best Model) - Loss: 1.0402 - Accuracy: 0.5000 - F1: 0.4378
sub_16:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.6765 - F1: 0.6832
sub_19:Test (Best Model) - Loss: 1.5954 - Accuracy: 0.2206 - F1: 0.2496
sub_4:Test (Best Model) - Loss: 0.8609 - Accuracy: 0.5652 - F1: 0.5619
sub_28:Test (Best Model) - Loss: 1.1430 - Accuracy: 0.4706 - F1: 0.4483
sub_8:Test (Best Model) - Loss: 0.9519 - Accuracy: 0.6471 - F1: 0.5862
sub_10:Test (Best Model) - Loss: 1.4495 - Accuracy: 0.2647 - F1: 0.2077
sub_12:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.6765 - F1: 0.6295
sub_2:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.4493 - F1: 0.3968
sub_9:Test (Best Model) - Loss: 0.8194 - Accuracy: 0.6471 - F1: 0.6518
sub_13:Test (Best Model) - Loss: 0.9210 - Accuracy: 0.5147 - F1: 0.4715
sub_14:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.4559 - F1: 0.3640
sub_18:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6522 - F1: 0.5987
sub_23:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.5652 - F1: 0.5273
sub_22:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.4412 - F1: 0.3813
sub_17:Test (Best Model) - Loss: 0.7571 - Accuracy: 0.7101 - F1: 0.7058
sub_29:Test (Best Model) - Loss: 0.8695 - Accuracy: 0.5882 - F1: 0.5811
sub_1:Test (Best Model) - Loss: 0.8558 - Accuracy: 0.6324 - F1: 0.6103
sub_21:Test (Best Model) - Loss: 0.4116 - Accuracy: 0.8676 - F1: 0.8675
sub_27:Test (Best Model) - Loss: 0.7571 - Accuracy: 0.7101 - F1: 0.7058
sub_16:Test (Best Model) - Loss: 0.7721 - Accuracy: 0.7206 - F1: 0.7232
sub_4:Test (Best Model) - Loss: 0.8811 - Accuracy: 0.6087 - F1: 0.5673
sub_8:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.6471 - F1: 0.5750
sub_26:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.7536 - F1: 0.7559
sub_5:Test (Best Model) - Loss: 0.9476 - Accuracy: 0.6912 - F1: 0.6641
sub_24:Test (Best Model) - Loss: 0.9194 - Accuracy: 0.5441 - F1: 0.5373
sub_6:Test (Best Model) - Loss: 1.0421 - Accuracy: 0.5000 - F1: 0.4579
sub_11:Test (Best Model) - Loss: 0.7487 - Accuracy: 0.6812 - F1: 0.6657
sub_25:Test (Best Model) - Loss: 0.3634 - Accuracy: 0.9275 - F1: 0.9251
sub_20:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.5588 - F1: 0.5276
sub_10:Test (Best Model) - Loss: 0.8907 - Accuracy: 0.6029 - F1: 0.5844
sub_19:Test (Best Model) - Loss: 1.2713 - Accuracy: 0.4853 - F1: 0.5135
sub_7:Test (Best Model) - Loss: 0.3679 - Accuracy: 0.9559 - F1: 0.9531
sub_3:Test (Best Model) - Loss: 0.7563 - Accuracy: 0.7941 - F1: 0.8035
sub_28:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.3676 - F1: 0.3307
sub_2:Test (Best Model) - Loss: 0.7840 - Accuracy: 0.7391 - F1: 0.7108
sub_12:Test (Best Model) - Loss: 0.7603 - Accuracy: 0.6029 - F1: 0.5842
sub_22:Test (Best Model) - Loss: 1.0557 - Accuracy: 0.4853 - F1: 0.4474
sub_1:Test (Best Model) - Loss: 0.9791 - Accuracy: 0.5000 - F1: 0.4631
sub_15:Test (Best Model) - Loss: 0.4670 - Accuracy: 0.8088 - F1: 0.8168
sub_23:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.7391 - F1: 0.7211
sub_4:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6522 - F1: 0.6275
sub_9:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.7647 - F1: 0.7699
sub_14:Test (Best Model) - Loss: 1.8460 - Accuracy: 0.4265 - F1: 0.3400
sub_18:Test (Best Model) - Loss: 0.9580 - Accuracy: 0.5072 - F1: 0.4432
sub_8:Test (Best Model) - Loss: 1.1879 - Accuracy: 0.6471 - F1: 0.5987
sub_5:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.1765 - F1: 0.2509
sub_11:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.8696 - F1: 0.8699
sub_24:Test (Best Model) - Loss: 1.0424 - Accuracy: 0.4853 - F1: 0.4489
sub_19:Test (Best Model) - Loss: 1.4347 - Accuracy: 0.3235 - F1: 0.3145
sub_26:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7246 - F1: 0.7196
sub_13:Test (Best Model) - Loss: 1.1790 - Accuracy: 0.4559 - F1: 0.3808
sub_16:Test (Best Model) - Loss: 0.7945 - Accuracy: 0.6912 - F1: 0.7088
sub_25:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9855 - F1: 0.9846
sub_29:Test (Best Model) - Loss: 0.8649 - Accuracy: 0.5588 - F1: 0.5825
sub_20:Test (Best Model) - Loss: 1.0589 - Accuracy: 0.4706 - F1: 0.4320
sub_10:Test (Best Model) - Loss: 1.0271 - Accuracy: 0.6029 - F1: 0.5997
sub_7:Test (Best Model) - Loss: 0.9921 - Accuracy: 0.5882 - F1: 0.5201
sub_2:Test (Best Model) - Loss: 0.7383 - Accuracy: 0.6029 - F1: 0.6003
sub_21:Test (Best Model) - Loss: 0.4598 - Accuracy: 0.8676 - F1: 0.8625
sub_6:Test (Best Model) - Loss: 1.3549 - Accuracy: 0.4706 - F1: 0.4353
sub_22:Test (Best Model) - Loss: 1.0726 - Accuracy: 0.3971 - F1: 0.3966
sub_3:Test (Best Model) - Loss: 0.8323 - Accuracy: 0.7500 - F1: 0.7458
sub_18:Test (Best Model) - Loss: 0.9685 - Accuracy: 0.4348 - F1: 0.3808
sub_12:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.6912 - F1: 0.6600
sub_26:Test (Best Model) - Loss: 0.9259 - Accuracy: 0.7059 - F1: 0.6886
sub_28:Test (Best Model) - Loss: 0.7711 - Accuracy: 0.7206 - F1: 0.6768
sub_17:Test (Best Model) - Loss: 0.4152 - Accuracy: 0.8551 - F1: 0.8559
sub_1:Test (Best Model) - Loss: 1.1558 - Accuracy: 0.4412 - F1: 0.4278
sub_24:Test (Best Model) - Loss: 0.7989 - Accuracy: 0.7500 - F1: 0.7641
sub_15:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.8382 - F1: 0.8472
sub_4:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.7681 - F1: 0.7197
sub_27:Test (Best Model) - Loss: 0.4152 - Accuracy: 0.8551 - F1: 0.8559
sub_8:Test (Best Model) - Loss: 0.9472 - Accuracy: 0.5588 - F1: 0.5332
sub_5:Test (Best Model) - Loss: 1.0626 - Accuracy: 0.6176 - F1: 0.5723
sub_23:Test (Best Model) - Loss: 0.8361 - Accuracy: 0.6377 - F1: 0.6268
sub_9:Test (Best Model) - Loss: 0.5492 - Accuracy: 0.7500 - F1: 0.7516
sub_16:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.4412 - F1: 0.4179
sub_19:Test (Best Model) - Loss: 1.8021 - Accuracy: 0.3088 - F1: 0.3166
sub_11:Test (Best Model) - Loss: 0.7104 - Accuracy: 0.7101 - F1: 0.6909
sub_6:Test (Best Model) - Loss: 1.1822 - Accuracy: 0.3913 - F1: 0.3796
sub_10:Test (Best Model) - Loss: 0.9733 - Accuracy: 0.6912 - F1: 0.6796
sub_25:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.9275 - F1: 0.9289
sub_29:Test (Best Model) - Loss: 0.8621 - Accuracy: 0.5588 - F1: 0.5603
sub_22:Test (Best Model) - Loss: 1.2213 - Accuracy: 0.5217 - F1: 0.4509
sub_13:Test (Best Model) - Loss: 1.1606 - Accuracy: 0.5441 - F1: 0.5013
sub_2:Test (Best Model) - Loss: 0.7368 - Accuracy: 0.7794 - F1: 0.7842
sub_14:Test (Best Model) - Loss: 1.5432 - Accuracy: 0.4853 - F1: 0.4306
sub_3:Test (Best Model) - Loss: 1.0308 - Accuracy: 0.5882 - F1: 0.5775
sub_18:Test (Best Model) - Loss: 1.0516 - Accuracy: 0.6029 - F1: 0.5307
sub_26:Test (Best Model) - Loss: 1.0732 - Accuracy: 0.3971 - F1: 0.3862
sub_12:Test (Best Model) - Loss: 0.9430 - Accuracy: 0.5797 - F1: 0.5736
sub_20:Test (Best Model) - Loss: 0.8635 - Accuracy: 0.6029 - F1: 0.5744
sub_7:Test (Best Model) - Loss: 0.7769 - Accuracy: 0.6618 - F1: 0.6082
sub_15:Test (Best Model) - Loss: 0.8658 - Accuracy: 0.6324 - F1: 0.6281
sub_1:Test (Best Model) - Loss: 1.1847 - Accuracy: 0.4638 - F1: 0.3714
sub_4:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.7971 - F1: 0.7859
sub_6:Test (Best Model) - Loss: 0.8105 - Accuracy: 0.6667 - F1: 0.6248
sub_24:Test (Best Model) - Loss: 0.9896 - Accuracy: 0.6029 - F1: 0.5371
sub_9:Test (Best Model) - Loss: 0.9488 - Accuracy: 0.5294 - F1: 0.5419
sub_28:Test (Best Model) - Loss: 1.2049 - Accuracy: 0.3824 - F1: 0.3013
sub_10:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.3088 - F1: 0.1967
sub_22:Test (Best Model) - Loss: 1.1146 - Accuracy: 0.5507 - F1: 0.5007
sub_19:Test (Best Model) - Loss: 1.0719 - Accuracy: 0.6029 - F1: 0.5364
sub_21:Test (Best Model) - Loss: 0.6223 - Accuracy: 0.7941 - F1: 0.8062
sub_17:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7536 - F1: 0.7572
sub_26:Test (Best Model) - Loss: 1.1096 - Accuracy: 0.4853 - F1: 0.4689
sub_27:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7536 - F1: 0.7572
sub_5:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.8088 - F1: 0.8001
sub_8:Test (Best Model) - Loss: 1.1571 - Accuracy: 0.5882 - F1: 0.5294
sub_14:Test (Best Model) - Loss: 1.0657 - Accuracy: 0.3971 - F1: 0.3912
sub_11:Test (Best Model) - Loss: 0.9169 - Accuracy: 0.6522 - F1: 0.5720
sub_18:Test (Best Model) - Loss: 1.0330 - Accuracy: 0.5735 - F1: 0.5192
sub_16:Test (Best Model) - Loss: 0.8414 - Accuracy: 0.6765 - F1: 0.6658
sub_2:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.7353 - F1: 0.7268
sub_29:Test (Best Model) - Loss: 0.9150 - Accuracy: 0.5294 - F1: 0.4335
sub_3:Test (Best Model) - Loss: 1.0883 - Accuracy: 0.5652 - F1: 0.5252
sub_23:Test (Best Model) - Loss: 0.8462 - Accuracy: 0.5072 - F1: 0.4379
sub_7:Test (Best Model) - Loss: 0.9971 - Accuracy: 0.6618 - F1: 0.5960
sub_25:Test (Best Model) - Loss: 0.8598 - Accuracy: 0.7059 - F1: 0.6584
sub_10:Test (Best Model) - Loss: 1.2953 - Accuracy: 0.4265 - F1: 0.3403
sub_26:Test (Best Model) - Loss: 1.0130 - Accuracy: 0.5882 - F1: 0.5262
sub_20:Test (Best Model) - Loss: 0.9650 - Accuracy: 0.7059 - F1: 0.6420
sub_12:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.7681 - F1: 0.7644
sub_13:Test (Best Model) - Loss: 1.2438 - Accuracy: 0.4118 - F1: 0.3561
sub_6:Test (Best Model) - Loss: 0.8498 - Accuracy: 0.6667 - F1: 0.6197
sub_8:Test (Best Model) - Loss: 0.8906 - Accuracy: 0.6765 - F1: 0.6143
sub_21:Test (Best Model) - Loss: 0.6218 - Accuracy: 0.7353 - F1: 0.6982
sub_15:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.7059 - F1: 0.6768
sub_22:Test (Best Model) - Loss: 1.0789 - Accuracy: 0.5072 - F1: 0.5095
sub_4:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.8551 - F1: 0.8539
sub_18:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.4412 - F1: 0.4212
sub_5:Test (Best Model) - Loss: 0.7761 - Accuracy: 0.8382 - F1: 0.8471
sub_23:Test (Best Model) - Loss: 1.2038 - Accuracy: 0.4265 - F1: 0.3945
sub_28:Test (Best Model) - Loss: 1.2163 - Accuracy: 0.3382 - F1: 0.2346
sub_17:Test (Best Model) - Loss: 1.1140 - Accuracy: 0.5942 - F1: 0.5539
sub_16:Test (Best Model) - Loss: 0.9515 - Accuracy: 0.6176 - F1: 0.5823
sub_2:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.7059 - F1: 0.7170
sub_19:Test (Best Model) - Loss: 0.8006 - Accuracy: 0.6618 - F1: 0.6358
sub_27:Test (Best Model) - Loss: 1.1140 - Accuracy: 0.5942 - F1: 0.5539
sub_24:Test (Best Model) - Loss: 0.7476 - Accuracy: 0.7500 - F1: 0.7322
sub_7:Test (Best Model) - Loss: 0.8918 - Accuracy: 0.6912 - F1: 0.6445
sub_14:Test (Best Model) - Loss: 0.8863 - Accuracy: 0.4706 - F1: 0.3931
sub_10:Test (Best Model) - Loss: 1.1914 - Accuracy: 0.2794 - F1: 0.2824
sub_12:Test (Best Model) - Loss: 0.9071 - Accuracy: 0.6812 - F1: 0.6434
sub_25:Test (Best Model) - Loss: 0.7484 - Accuracy: 0.6765 - F1: 0.6346
sub_26:Test (Best Model) - Loss: 1.0644 - Accuracy: 0.5441 - F1: 0.5091
sub_11:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.6377 - F1: 0.5679
sub_29:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.6029 - F1: 0.5799
sub_9:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6765 - F1: 0.6622
sub_3:Test (Best Model) - Loss: 0.9065 - Accuracy: 0.6957 - F1: 0.6247
sub_22:Test (Best Model) - Loss: 1.2114 - Accuracy: 0.5072 - F1: 0.4764
sub_1:Test (Best Model) - Loss: 0.7470 - Accuracy: 0.6812 - F1: 0.6793
sub_6:Test (Best Model) - Loss: 0.7955 - Accuracy: 0.6667 - F1: 0.6305
sub_4:Test (Best Model) - Loss: 0.4738 - Accuracy: 0.8406 - F1: 0.8442
sub_21:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.7941 - F1: 0.7893
sub_5:Test (Best Model) - Loss: 1.0461 - Accuracy: 0.5588 - F1: 0.5095
sub_8:Test (Best Model) - Loss: 0.8336 - Accuracy: 0.7206 - F1: 0.6528
sub_15:Test (Best Model) - Loss: 1.0328 - Accuracy: 0.4559 - F1: 0.3936
sub_13:Test (Best Model) - Loss: 1.1141 - Accuracy: 0.5797 - F1: 0.5412
sub_18:Test (Best Model) - Loss: 1.1237 - Accuracy: 0.4853 - F1: 0.4117
sub_17:Test (Best Model) - Loss: 1.1004 - Accuracy: 0.5507 - F1: 0.5460
sub_20:Test (Best Model) - Loss: 0.8712 - Accuracy: 0.6618 - F1: 0.6233
sub_27:Test (Best Model) - Loss: 1.1004 - Accuracy: 0.5507 - F1: 0.5460
sub_28:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.3971 - F1: 0.3189
sub_23:Test (Best Model) - Loss: 0.9809 - Accuracy: 0.5588 - F1: 0.5251
sub_24:Test (Best Model) - Loss: 1.0420 - Accuracy: 0.6765 - F1: 0.6021
sub_2:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.7059 - F1: 0.7083
sub_14:Test (Best Model) - Loss: 0.9591 - Accuracy: 0.6029 - F1: 0.6288
sub_25:Test (Best Model) - Loss: 0.8190 - Accuracy: 0.6912 - F1: 0.6421
sub_10:Test (Best Model) - Loss: 1.1722 - Accuracy: 0.4706 - F1: 0.4305
sub_12:Test (Best Model) - Loss: 0.8190 - Accuracy: 0.6812 - F1: 0.6888
sub_6:Test (Best Model) - Loss: 0.9484 - Accuracy: 0.5507 - F1: 0.5619
sub_9:Test (Best Model) - Loss: 0.8934 - Accuracy: 0.6324 - F1: 0.5915
sub_7:Test (Best Model) - Loss: 0.9754 - Accuracy: 0.6471 - F1: 0.6159
sub_26:Test (Best Model) - Loss: 0.7730 - Accuracy: 0.6765 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 0.9816 - Accuracy: 0.5652 - F1: 0.5731
sub_19:Test (Best Model) - Loss: 0.9180 - Accuracy: 0.6618 - F1: 0.6775
sub_16:Test (Best Model) - Loss: 0.9256 - Accuracy: 0.6176 - F1: 0.6481
sub_4:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.7536 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.6393 - Accuracy: 0.8696 - F1: 0.8705
sub_15:Test (Best Model) - Loss: 0.9900 - Accuracy: 0.5588 - F1: 0.5272
sub_8:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.7647 - F1: 0.7466
sub_18:Test (Best Model) - Loss: 1.1239 - Accuracy: 0.4265 - F1: 0.3467
sub_24:Test (Best Model) - Loss: 0.8895 - Accuracy: 0.7059 - F1: 0.6266
sub_17:Test (Best Model) - Loss: 1.0447 - Accuracy: 0.4783 - F1: 0.4619
sub_23:Test (Best Model) - Loss: 1.2033 - Accuracy: 0.4706 - F1: 0.3222
sub_27:Test (Best Model) - Loss: 1.0447 - Accuracy: 0.4783 - F1: 0.4619
sub_1:Test (Best Model) - Loss: 0.8182 - Accuracy: 0.6957 - F1: 0.6966
sub_2:Test (Best Model) - Loss: 0.8123 - Accuracy: 0.5507 - F1: 0.5057
sub_29:Test (Best Model) - Loss: 0.7520 - Accuracy: 0.5588 - F1: 0.4826
sub_28:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.3676 - F1: 0.3667
sub_10:Test (Best Model) - Loss: 0.9555 - Accuracy: 0.4928 - F1: 0.3839
sub_5:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.8088 - F1: 0.8022
sub_21:Test (Best Model) - Loss: 0.5122 - Accuracy: 0.7353 - F1: 0.6987
sub_13:Test (Best Model) - Loss: 1.2954 - Accuracy: 0.3188 - F1: 0.2447
sub_22:Test (Best Model) - Loss: 0.9818 - Accuracy: 0.5882 - F1: 0.5272
sub_20:Test (Best Model) - Loss: 0.8615 - Accuracy: 0.6176 - F1: 0.5760
sub_14:Test (Best Model) - Loss: 0.8974 - Accuracy: 0.6912 - F1: 0.6942
sub_6:Test (Best Model) - Loss: 0.7652 - Accuracy: 0.7101 - F1: 0.6943
sub_25:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.8235 - F1: 0.8125
sub_7:Test (Best Model) - Loss: 0.9092 - Accuracy: 0.7353 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.7235 - Accuracy: 0.7206 - F1: 0.7273
sub_3:Test (Best Model) - Loss: 0.8071 - Accuracy: 0.6087 - F1: 0.6066
sub_26:Test (Best Model) - Loss: 0.8477 - Accuracy: 0.5588 - F1: 0.5347
sub_12:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.6667 - F1: 0.6890
sub_9:Test (Best Model) - Loss: 1.1629 - Accuracy: 0.4412 - F1: 0.2971
sub_16:Test (Best Model) - Loss: 1.1958 - Accuracy: 0.4265 - F1: 0.3971
sub_4:Test (Best Model) - Loss: 0.7701 - Accuracy: 0.6377 - F1: 0.5940
sub_8:Test (Best Model) - Loss: 1.0947 - Accuracy: 0.5294 - F1: 0.5265
sub_17:Test (Best Model) - Loss: 1.0635 - Accuracy: 0.5072 - F1: 0.4928
sub_19:Test (Best Model) - Loss: 0.8104 - Accuracy: 0.6765 - F1: 0.6635
sub_27:Test (Best Model) - Loss: 1.0635 - Accuracy: 0.5072 - F1: 0.4928
sub_11:Test (Best Model) - Loss: 1.1036 - Accuracy: 0.5797 - F1: 0.5067
sub_23:Test (Best Model) - Loss: 1.2761 - Accuracy: 0.4559 - F1: 0.3208
sub_2:Test (Best Model) - Loss: 0.8140 - Accuracy: 0.6957 - F1: 0.6890
sub_18:Test (Best Model) - Loss: 1.1553 - Accuracy: 0.4706 - F1: 0.3982
sub_24:Test (Best Model) - Loss: 0.9479 - Accuracy: 0.6324 - F1: 0.5784
sub_1:Test (Best Model) - Loss: 0.9360 - Accuracy: 0.5217 - F1: 0.4627
sub_22:Test (Best Model) - Loss: 0.9685 - Accuracy: 0.6176 - F1: 0.5806
sub_6:Test (Best Model) - Loss: 1.0319 - Accuracy: 0.6522 - F1: 0.5724
sub_29:Test (Best Model) - Loss: 0.6271 - Accuracy: 0.8088 - F1: 0.8070
sub_28:Test (Best Model) - Loss: 2.0693 - Accuracy: 0.4118 - F1: 0.3268
sub_12:Test (Best Model) - Loss: 0.9692 - Accuracy: 0.6176 - F1: 0.5879
sub_16:Test (Best Model) - Loss: 0.8488 - Accuracy: 0.7206 - F1: 0.7123
sub_14:Test (Best Model) - Loss: 1.0224 - Accuracy: 0.3676 - F1: 0.4020
sub_10:Test (Best Model) - Loss: 0.9134 - Accuracy: 0.5942 - F1: 0.5449
sub_5:Test (Best Model) - Loss: 0.7259 - Accuracy: 0.7647 - F1: 0.6976
sub_21:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.8088 - F1: 0.7955
sub_15:Test (Best Model) - Loss: 0.8678 - Accuracy: 0.6765 - F1: 0.5907
sub_4:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.7391 - F1: 0.7038
sub_8:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.5441 - F1: 0.5490
sub_20:Test (Best Model) - Loss: 0.7313 - Accuracy: 0.6765 - F1: 0.6287
sub_7:Test (Best Model) - Loss: 0.9933 - Accuracy: 0.6765 - F1: 0.6218
sub_26:Test (Best Model) - Loss: 1.0655 - Accuracy: 0.4853 - F1: 0.5117
sub_9:Test (Best Model) - Loss: 0.8549 - Accuracy: 0.4853 - F1: 0.4278
sub_3:Test (Best Model) - Loss: 0.8725 - Accuracy: 0.6667 - F1: 0.6233
sub_25:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.7059 - F1: 0.6492
sub_17:Test (Best Model) - Loss: 1.0835 - Accuracy: 0.5797 - F1: 0.5362
sub_2:Test (Best Model) - Loss: 0.8605 - Accuracy: 0.6667 - F1: 0.6032
sub_13:Test (Best Model) - Loss: 1.1346 - Accuracy: 0.4493 - F1: 0.3972
sub_23:Test (Best Model) - Loss: 1.1923 - Accuracy: 0.3529 - F1: 0.2661
sub_27:Test (Best Model) - Loss: 1.0835 - Accuracy: 0.5797 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.7623 - Accuracy: 0.6324 - F1: 0.6260
sub_18:Test (Best Model) - Loss: 0.9268 - Accuracy: 0.5882 - F1: 0.5429
sub_11:Test (Best Model) - Loss: 0.7991 - Accuracy: 0.7246 - F1: 0.6836
sub_6:Test (Best Model) - Loss: 0.9089 - Accuracy: 0.7101 - F1: 0.6500
sub_22:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.4118 - F1: 0.4241
sub_20:Test (Best Model) - Loss: 0.8081 - Accuracy: 0.7059 - F1: 0.6342
sub_24:Test (Best Model) - Loss: 0.5645 - Accuracy: 0.7647 - F1: 0.7683
sub_1:Test (Best Model) - Loss: 0.7842 - Accuracy: 0.7246 - F1: 0.7361
sub_4:Test (Best Model) - Loss: 0.9004 - Accuracy: 0.7246 - F1: 0.6523
sub_14:Test (Best Model) - Loss: 0.7974 - Accuracy: 0.6618 - F1: 0.6582
sub_16:Test (Best Model) - Loss: 1.0412 - Accuracy: 0.5147 - F1: 0.5075
sub_26:Test (Best Model) - Loss: 1.0042 - Accuracy: 0.6176 - F1: 0.6279
sub_12:Test (Best Model) - Loss: 0.9750 - Accuracy: 0.6765 - F1: 0.6822
sub_10:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.7681 - F1: 0.7606
sub_8:Test (Best Model) - Loss: 1.0737 - Accuracy: 0.6471 - F1: 0.5967
sub_15:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.5147 - F1: 0.4011
sub_5:Test (Best Model) - Loss: 1.2056 - Accuracy: 0.5882 - F1: 0.5284
sub_28:Test (Best Model) - Loss: 1.1462 - Accuracy: 0.4412 - F1: 0.3713
sub_3:Test (Best Model) - Loss: 1.0302 - Accuracy: 0.5652 - F1: 0.4895
sub_25:Test (Best Model) - Loss: 0.8240 - Accuracy: 0.6765 - F1: 0.6648
sub_7:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.6324 - F1: 0.6117
sub_21:Test (Best Model) - Loss: 0.4910 - Accuracy: 0.8529 - F1: 0.8509
sub_9:Test (Best Model) - Loss: 0.8990 - Accuracy: 0.4706 - F1: 0.4327
sub_29:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.7941 - F1: 0.7893
sub_22:Test (Best Model) - Loss: 0.9854 - Accuracy: 0.4853 - F1: 0.5199
sub_18:Test (Best Model) - Loss: 0.9183 - Accuracy: 0.6176 - F1: 0.6296
sub_2:Test (Best Model) - Loss: 0.8812 - Accuracy: 0.5072 - F1: 0.4599
sub_6:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.7101 - F1: 0.6617
sub_20:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.6232 - F1: 0.5729
sub_19:Test (Best Model) - Loss: 0.9381 - Accuracy: 0.5294 - F1: 0.4836
sub_23:Test (Best Model) - Loss: 1.1571 - Accuracy: 0.4058 - F1: 0.4031
sub_16:Test (Best Model) - Loss: 0.7666 - Accuracy: 0.7941 - F1: 0.7931
sub_17:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.6912 - F1: 0.6996
sub_4:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.7246 - F1: 0.6789
sub_10:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.8551 - F1: 0.8475
sub_26:Test (Best Model) - Loss: 0.8893 - Accuracy: 0.6029 - F1: 0.6417
sub_13:Test (Best Model) - Loss: 1.1700 - Accuracy: 0.4638 - F1: 0.4044
sub_14:Test (Best Model) - Loss: 0.9363 - Accuracy: 0.5000 - F1: 0.4884
sub_27:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.6912 - F1: 0.6996
sub_8:Test (Best Model) - Loss: 0.9918 - Accuracy: 0.6176 - F1: 0.5756
sub_28:Test (Best Model) - Loss: 1.6786 - Accuracy: 0.2206 - F1: 0.1142
sub_1:Test (Best Model) - Loss: 1.4562 - Accuracy: 0.5882 - F1: 0.5117
sub_12:Test (Best Model) - Loss: 0.8706 - Accuracy: 0.7206 - F1: 0.7087
sub_18:Test (Best Model) - Loss: 1.0841 - Accuracy: 0.4706 - F1: 0.4751
sub_24:Test (Best Model) - Loss: 0.7969 - Accuracy: 0.7353 - F1: 0.7506
sub_2:Test (Best Model) - Loss: 0.8315 - Accuracy: 0.6667 - F1: 0.6715
sub_7:Test (Best Model) - Loss: 1.0062 - Accuracy: 0.5147 - F1: 0.4405
sub_20:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.7681 - F1: 0.7735
sub_15:Test (Best Model) - Loss: 1.2330 - Accuracy: 0.5882 - F1: 0.5149
sub_6:Test (Best Model) - Loss: 0.5705 - Accuracy: 0.7826 - F1: 0.7828
sub_4:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.7681 - F1: 0.7497
sub_17:Test (Best Model) - Loss: 0.9387 - Accuracy: 0.6765 - F1: 0.6251
sub_5:Test (Best Model) - Loss: 1.5346 - Accuracy: 0.4706 - F1: 0.3843
sub_22:Test (Best Model) - Loss: 1.0067 - Accuracy: 0.5735 - F1: 0.5730
sub_25:Test (Best Model) - Loss: 0.7550 - Accuracy: 0.7353 - F1: 0.7468
sub_19:Test (Best Model) - Loss: 0.9962 - Accuracy: 0.5441 - F1: 0.4942
sub_10:Test (Best Model) - Loss: 0.8655 - Accuracy: 0.6522 - F1: 0.6410
sub_9:Test (Best Model) - Loss: 0.8310 - Accuracy: 0.5882 - F1: 0.5440
sub_11:Test (Best Model) - Loss: 1.0045 - Accuracy: 0.5652 - F1: 0.5130
sub_14:Test (Best Model) - Loss: 0.9375 - Accuracy: 0.6471 - F1: 0.5833
sub_21:Test (Best Model) - Loss: 0.2833 - Accuracy: 0.9412 - F1: 0.9333
sub_16:Test (Best Model) - Loss: 0.8664 - Accuracy: 0.7353 - F1: 0.7296
sub_29:Test (Best Model) - Loss: 0.8403 - Accuracy: 0.6522 - F1: 0.6336
sub_23:Test (Best Model) - Loss: 1.2554 - Accuracy: 0.4348 - F1: 0.3598
sub_27:Test (Best Model) - Loss: 0.9387 - Accuracy: 0.6765 - F1: 0.6251
sub_28:Test (Best Model) - Loss: 1.7768 - Accuracy: 0.4559 - F1: 0.3084
sub_8:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.6618 - F1: 0.6538
sub_3:Test (Best Model) - Loss: 0.7516 - Accuracy: 0.7681 - F1: 0.7719
sub_1:Test (Best Model) - Loss: 1.0734 - Accuracy: 0.5147 - F1: 0.4589
sub_12:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.7500 - F1: 0.7547
sub_20:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.7536 - F1: 0.7415
sub_24:Test (Best Model) - Loss: 0.8744 - Accuracy: 0.6324 - F1: 0.6396
sub_18:Test (Best Model) - Loss: 1.0068 - Accuracy: 0.5588 - F1: 0.5010
sub_14:Test (Best Model) - Loss: 0.9449 - Accuracy: 0.6029 - F1: 0.5682
sub_13:Test (Best Model) - Loss: 0.9256 - Accuracy: 0.6377 - F1: 0.5797
sub_16:Test (Best Model) - Loss: 0.8674 - Accuracy: 0.7206 - F1: 0.7225
sub_5:Test (Best Model) - Loss: 1.0195 - Accuracy: 0.6029 - F1: 0.5386
sub_25:Test (Best Model) - Loss: 0.9392 - Accuracy: 0.6765 - F1: 0.6137
sub_28:Test (Best Model) - Loss: 1.4174 - Accuracy: 0.3824 - F1: 0.3032
sub_7:Test (Best Model) - Loss: 0.8315 - Accuracy: 0.7059 - F1: 0.6994
sub_24:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.7353 - F1: 0.7556
sub_17:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.6471 - F1: 0.6122
sub_12:Test (Best Model) - Loss: 0.7525 - Accuracy: 0.6912 - F1: 0.6789
sub_23:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.5507 - F1: 0.4888
sub_14:Test (Best Model) - Loss: 0.9381 - Accuracy: 0.7059 - F1: 0.6386
sub_20:Test (Best Model) - Loss: 0.8970 - Accuracy: 0.5797 - F1: 0.5385
sub_9:Test (Best Model) - Loss: 0.8559 - Accuracy: 0.6765 - F1: 0.6800
sub_29:Test (Best Model) - Loss: 0.9805 - Accuracy: 0.6232 - F1: 0.6144
sub_15:Test (Best Model) - Loss: 0.9760 - Accuracy: 0.6912 - F1: 0.6384
sub_21:Test (Best Model) - Loss: 0.6272 - Accuracy: 0.7059 - F1: 0.6376
sub_27:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.6471 - F1: 0.6122
sub_1:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.7059 - F1: 0.6280
sub_3:Test (Best Model) - Loss: 1.1510 - Accuracy: 0.4638 - F1: 0.3881
sub_28:Test (Best Model) - Loss: 0.9696 - Accuracy: 0.5441 - F1: 0.4924
sub_11:Test (Best Model) - Loss: 0.8844 - Accuracy: 0.6812 - F1: 0.6552
sub_7:Test (Best Model) - Loss: 0.7915 - Accuracy: 0.7647 - F1: 0.7641
sub_20:Test (Best Model) - Loss: 0.7950 - Accuracy: 0.6667 - F1: 0.6301
sub_19:Test (Best Model) - Loss: 1.0752 - Accuracy: 0.4559 - F1: 0.4208
sub_28:Test (Best Model) - Loss: 1.5474 - Accuracy: 0.2059 - F1: 0.1567
sub_13:Test (Best Model) - Loss: 1.1577 - Accuracy: 0.5294 - F1: 0.4575
sub_25:Test (Best Model) - Loss: 0.7573 - Accuracy: 0.6618 - F1: 0.6177
sub_5:Test (Best Model) - Loss: 0.8775 - Accuracy: 0.6912 - F1: 0.6279
sub_17:Test (Best Model) - Loss: 0.8129 - Accuracy: 0.7206 - F1: 0.6914
sub_9:Test (Best Model) - Loss: 1.1048 - Accuracy: 0.4559 - F1: 0.3906
sub_23:Test (Best Model) - Loss: 1.1924 - Accuracy: 0.5362 - F1: 0.4906
sub_27:Test (Best Model) - Loss: 0.8129 - Accuracy: 0.7206 - F1: 0.6914
sub_15:Test (Best Model) - Loss: 1.1201 - Accuracy: 0.5294 - F1: 0.4671
sub_21:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.7206 - F1: 0.6885
sub_3:Test (Best Model) - Loss: 0.9063 - Accuracy: 0.5942 - F1: 0.6052
sub_29:Test (Best Model) - Loss: 1.0179 - Accuracy: 0.6087 - F1: 0.5642
sub_7:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.8529 - F1: 0.8529
sub_1:Test (Best Model) - Loss: 0.9270 - Accuracy: 0.6029 - F1: 0.5718
sub_25:Test (Best Model) - Loss: 0.7503 - Accuracy: 0.6471 - F1: 0.6373
sub_19:Test (Best Model) - Loss: 1.0618 - Accuracy: 0.3971 - F1: 0.3209
sub_11:Test (Best Model) - Loss: 1.1072 - Accuracy: 0.4783 - F1: 0.4347
sub_9:Test (Best Model) - Loss: 1.0310 - Accuracy: 0.4853 - F1: 0.4285
sub_23:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.3913 - F1: 0.3236
sub_5:Test (Best Model) - Loss: 1.4251 - Accuracy: 0.4706 - F1: 0.3464
sub_29:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.5797 - F1: 0.5189
sub_13:Test (Best Model) - Loss: 1.6681 - Accuracy: 0.3088 - F1: 0.2376
sub_17:Test (Best Model) - Loss: 0.8483 - Accuracy: 0.5294 - F1: 0.5175
sub_27:Test (Best Model) - Loss: 0.8483 - Accuracy: 0.5294 - F1: 0.5175
sub_3:Test (Best Model) - Loss: 0.8641 - Accuracy: 0.5942 - F1: 0.5482
sub_15:Test (Best Model) - Loss: 1.1311 - Accuracy: 0.5147 - F1: 0.4043
sub_21:Test (Best Model) - Loss: 0.4137 - Accuracy: 0.8529 - F1: 0.8484
sub_19:Test (Best Model) - Loss: 1.0278 - Accuracy: 0.4559 - F1: 0.4150
sub_11:Test (Best Model) - Loss: 0.4531 - Accuracy: 0.8696 - F1: 0.8711
sub_1:Test (Best Model) - Loss: 0.8227 - Accuracy: 0.6765 - F1: 0.6128
sub_29:Test (Best Model) - Loss: 1.0680 - Accuracy: 0.3478 - F1: 0.3848
sub_9:Test (Best Model) - Loss: 0.9155 - Accuracy: 0.6765 - F1: 0.6725
sub_13:Test (Best Model) - Loss: 1.4857 - Accuracy: 0.4559 - F1: 0.3456
sub_3:Test (Best Model) - Loss: 0.9883 - Accuracy: 0.5942 - F1: 0.5871
sub_11:Test (Best Model) - Loss: 0.9939 - Accuracy: 0.5507 - F1: 0.5354
sub_21:Test (Best Model) - Loss: 0.3522 - Accuracy: 0.9265 - F1: 0.9257
sub_13:Test (Best Model) - Loss: 1.2779 - Accuracy: 0.4265 - F1: 0.3733
sub_13:Test (Best Model) - Loss: 1.2992 - Accuracy: 0.4559 - F1: 0.3808

=== Summary Results ===

acc: 61.00 ± 8.93
F1: 57.81 ± 9.83
acc-in: 91.67 ± 3.17
F1-in: 91.38 ± 3.26
