lr: 0.0001
sub_17:Test (Best Model) - Loss: 0.3661 - Accuracy: 0.8696 - F1: 0.8654
sub_19:Test (Best Model) - Loss: 2.9275 - Accuracy: 0.4412 - F1: 0.3382
sub_4:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.6667 - F1: 0.6262
sub_13:Test (Best Model) - Loss: 0.7492 - Accuracy: 0.6471 - F1: 0.6035
sub_27:Test (Best Model) - Loss: 0.3661 - Accuracy: 0.8696 - F1: 0.8654
sub_3:Test (Best Model) - Loss: 0.8253 - Accuracy: 0.7353 - F1: 0.7384
sub_24:Test (Best Model) - Loss: 0.8287 - Accuracy: 0.7059 - F1: 0.6914
sub_14:Test (Best Model) - Loss: 2.4035 - Accuracy: 0.4559 - F1: 0.3941
sub_8:Test (Best Model) - Loss: 2.2109 - Accuracy: 0.6912 - F1: 0.6200
sub_12:Test (Best Model) - Loss: 0.8862 - Accuracy: 0.6912 - F1: 0.6888
sub_6:Test (Best Model) - Loss: 1.9296 - Accuracy: 0.5294 - F1: 0.4916
sub_5:Test (Best Model) - Loss: 2.6733 - Accuracy: 0.5000 - F1: 0.4403
sub_7:Test (Best Model) - Loss: 0.2180 - Accuracy: 0.9265 - F1: 0.9236
sub_23:Test (Best Model) - Loss: 0.5509 - Accuracy: 0.8696 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 1.1128 - Accuracy: 0.6957 - F1: 0.6957
sub_29:Test (Best Model) - Loss: 1.6496 - Accuracy: 0.4559 - F1: 0.5006
sub_10:Test (Best Model) - Loss: 2.7203 - Accuracy: 0.4559 - F1: 0.5063
sub_20:Test (Best Model) - Loss: 1.4203 - Accuracy: 0.7206 - F1: 0.6728
sub_2:Test (Best Model) - Loss: 0.8804 - Accuracy: 0.7681 - F1: 0.7644
sub_26:Test (Best Model) - Loss: 1.2532 - Accuracy: 0.6522 - F1: 0.6531
sub_22:Test (Best Model) - Loss: 2.7310 - Accuracy: 0.5441 - F1: 0.4861
sub_1:Test (Best Model) - Loss: 1.7089 - Accuracy: 0.5735 - F1: 0.5555
sub_9:Test (Best Model) - Loss: 1.0285 - Accuracy: 0.6324 - F1: 0.6635
sub_16:Test (Best Model) - Loss: 1.3518 - Accuracy: 0.7353 - F1: 0.7379
sub_11:Test (Best Model) - Loss: 0.8577 - Accuracy: 0.7391 - F1: 0.7252
sub_17:Test (Best Model) - Loss: 0.7406 - Accuracy: 0.7826 - F1: 0.7868
sub_25:Test (Best Model) - Loss: 0.0279 - Accuracy: 0.9855 - F1: 0.9861
sub_27:Test (Best Model) - Loss: 0.7406 - Accuracy: 0.7826 - F1: 0.7868
sub_15:Test (Best Model) - Loss: 0.8227 - Accuracy: 0.7794 - F1: 0.7867
sub_8:Test (Best Model) - Loss: 1.1785 - Accuracy: 0.6765 - F1: 0.6023
sub_21:Test (Best Model) - Loss: 0.6041 - Accuracy: 0.8235 - F1: 0.8256
sub_24:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.6765 - F1: 0.6618
sub_14:Test (Best Model) - Loss: 3.7748 - Accuracy: 0.4412 - F1: 0.3759
sub_18:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.7681 - F1: 0.7736
sub_3:Test (Best Model) - Loss: 0.5439 - Accuracy: 0.8382 - F1: 0.8422
sub_28:Test (Best Model) - Loss: 1.8589 - Accuracy: 0.4853 - F1: 0.4359
sub_26:Test (Best Model) - Loss: 0.9896 - Accuracy: 0.6377 - F1: 0.6458
sub_16:Test (Best Model) - Loss: 1.0965 - Accuracy: 0.7500 - F1: 0.7491
sub_19:Test (Best Model) - Loss: 4.5005 - Accuracy: 0.3529 - F1: 0.3207
sub_7:Test (Best Model) - Loss: 0.1110 - Accuracy: 0.9412 - F1: 0.9365
sub_5:Test (Best Model) - Loss: 2.2498 - Accuracy: 0.7206 - F1: 0.6565
sub_6:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.6324 - F1: 0.6101
sub_4:Test (Best Model) - Loss: 1.7562 - Accuracy: 0.6667 - F1: 0.6097
sub_29:Test (Best Model) - Loss: 1.1618 - Accuracy: 0.6324 - F1: 0.6315
sub_12:Test (Best Model) - Loss: 0.9569 - Accuracy: 0.7647 - F1: 0.7671
sub_21:Test (Best Model) - Loss: 0.5081 - Accuracy: 0.8088 - F1: 0.8006
sub_20:Test (Best Model) - Loss: 1.2624 - Accuracy: 0.6618 - F1: 0.6183
sub_22:Test (Best Model) - Loss: 1.1595 - Accuracy: 0.6471 - F1: 0.5810
sub_23:Test (Best Model) - Loss: 1.3248 - Accuracy: 0.7826 - F1: 0.7821
sub_13:Test (Best Model) - Loss: 1.2412 - Accuracy: 0.5588 - F1: 0.5163
sub_11:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.7681 - F1: 0.7465
sub_8:Test (Best Model) - Loss: 1.7198 - Accuracy: 0.6176 - F1: 0.5883
sub_9:Test (Best Model) - Loss: 2.0310 - Accuracy: 0.5000 - F1: 0.5481
sub_10:Test (Best Model) - Loss: 2.5600 - Accuracy: 0.4706 - F1: 0.4990
sub_1:Test (Best Model) - Loss: 1.4909 - Accuracy: 0.6176 - F1: 0.6217
sub_2:Test (Best Model) - Loss: 1.0182 - Accuracy: 0.7246 - F1: 0.7119
sub_24:Test (Best Model) - Loss: 1.5860 - Accuracy: 0.6471 - F1: 0.6351
sub_25:Test (Best Model) - Loss: 0.0137 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.4843 - Accuracy: 0.8824 - F1: 0.8862
sub_17:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.8406 - F1: 0.8428
sub_27:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.8406 - F1: 0.8428
sub_20:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.5882 - F1: 0.5673
sub_7:Test (Best Model) - Loss: 1.0293 - Accuracy: 0.7647 - F1: 0.7229
sub_16:Test (Best Model) - Loss: 1.2394 - Accuracy: 0.6471 - F1: 0.6260
sub_18:Test (Best Model) - Loss: 1.2681 - Accuracy: 0.7391 - F1: 0.7255
sub_5:Test (Best Model) - Loss: 2.8187 - Accuracy: 0.6765 - F1: 0.6200
sub_14:Test (Best Model) - Loss: 3.3893 - Accuracy: 0.4412 - F1: 0.3541
sub_3:Test (Best Model) - Loss: 0.7736 - Accuracy: 0.7794 - F1: 0.7822
sub_4:Test (Best Model) - Loss: 1.6595 - Accuracy: 0.6232 - F1: 0.5981
sub_26:Test (Best Model) - Loss: 1.2108 - Accuracy: 0.6667 - F1: 0.6675
sub_21:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.8529 - F1: 0.8532
sub_23:Test (Best Model) - Loss: 0.5651 - Accuracy: 0.7971 - F1: 0.8014
sub_19:Test (Best Model) - Loss: 4.7087 - Accuracy: 0.3382 - F1: 0.2972
sub_28:Test (Best Model) - Loss: 2.0517 - Accuracy: 0.4559 - F1: 0.3638
sub_29:Test (Best Model) - Loss: 2.2185 - Accuracy: 0.6029 - F1: 0.5918
sub_11:Test (Best Model) - Loss: 0.8082 - Accuracy: 0.6957 - F1: 0.6779
sub_8:Test (Best Model) - Loss: 1.4592 - Accuracy: 0.6765 - F1: 0.6176
sub_12:Test (Best Model) - Loss: 1.6427 - Accuracy: 0.7059 - F1: 0.6503
sub_6:Test (Best Model) - Loss: 2.8314 - Accuracy: 0.4559 - F1: 0.4487
sub_22:Test (Best Model) - Loss: 2.2059 - Accuracy: 0.5882 - F1: 0.5395
sub_10:Test (Best Model) - Loss: 2.0922 - Accuracy: 0.4706 - F1: 0.4700
sub_17:Test (Best Model) - Loss: 0.2940 - Accuracy: 0.9275 - F1: 0.9292
sub_13:Test (Best Model) - Loss: 1.4582 - Accuracy: 0.5588 - F1: 0.5112
sub_25:Test (Best Model) - Loss: 0.0821 - Accuracy: 0.9710 - F1: 0.9707
sub_27:Test (Best Model) - Loss: 0.2940 - Accuracy: 0.9275 - F1: 0.9292
sub_2:Test (Best Model) - Loss: 0.7190 - Accuracy: 0.7101 - F1: 0.7021
sub_9:Test (Best Model) - Loss: 1.8535 - Accuracy: 0.6029 - F1: 0.6158
sub_24:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.6618 - F1: 0.6528
sub_1:Test (Best Model) - Loss: 2.2012 - Accuracy: 0.5000 - F1: 0.5031
sub_5:Test (Best Model) - Loss: 1.9586 - Accuracy: 0.7353 - F1: 0.6631
sub_16:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.7794 - F1: 0.7848
sub_15:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.6912 - F1: 0.6980
sub_20:Test (Best Model) - Loss: 1.3160 - Accuracy: 0.5735 - F1: 0.5350
sub_7:Test (Best Model) - Loss: 0.1381 - Accuracy: 0.9412 - F1: 0.9402
sub_26:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.7391 - F1: 0.7567
sub_23:Test (Best Model) - Loss: 0.4655 - Accuracy: 0.8261 - F1: 0.8261
sub_14:Test (Best Model) - Loss: 3.8838 - Accuracy: 0.4265 - F1: 0.3688
sub_3:Test (Best Model) - Loss: 0.9038 - Accuracy: 0.7647 - F1: 0.7538
sub_4:Test (Best Model) - Loss: 0.9941 - Accuracy: 0.6667 - F1: 0.6549
sub_18:Test (Best Model) - Loss: 1.7007 - Accuracy: 0.5942 - F1: 0.5879
sub_29:Test (Best Model) - Loss: 1.6301 - Accuracy: 0.5882 - F1: 0.6049
sub_21:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.8088 - F1: 0.8122
sub_19:Test (Best Model) - Loss: 4.5347 - Accuracy: 0.4706 - F1: 0.3681
sub_28:Test (Best Model) - Loss: 2.0604 - Accuracy: 0.5294 - F1: 0.4633
sub_11:Test (Best Model) - Loss: 0.5776 - Accuracy: 0.8696 - F1: 0.8638
sub_8:Test (Best Model) - Loss: 1.9901 - Accuracy: 0.6029 - F1: 0.5637
sub_6:Test (Best Model) - Loss: 1.4713 - Accuracy: 0.6912 - F1: 0.6906
sub_22:Test (Best Model) - Loss: 2.4361 - Accuracy: 0.5441 - F1: 0.4806
sub_10:Test (Best Model) - Loss: 1.1722 - Accuracy: 0.5441 - F1: 0.5799
sub_25:Test (Best Model) - Loss: 0.2254 - Accuracy: 0.9130 - F1: 0.9127
sub_12:Test (Best Model) - Loss: 1.8589 - Accuracy: 0.6765 - F1: 0.6124
sub_9:Test (Best Model) - Loss: 1.1903 - Accuracy: 0.6912 - F1: 0.6861
sub_27:Test (Best Model) - Loss: 0.8434 - Accuracy: 0.7681 - F1: 0.7737
sub_5:Test (Best Model) - Loss: 2.7065 - Accuracy: 0.6912 - F1: 0.6294
sub_17:Test (Best Model) - Loss: 0.8434 - Accuracy: 0.7681 - F1: 0.7737
sub_13:Test (Best Model) - Loss: 2.3956 - Accuracy: 0.5294 - F1: 0.4778
sub_2:Test (Best Model) - Loss: 1.4684 - Accuracy: 0.6812 - F1: 0.6355
sub_15:Test (Best Model) - Loss: 0.4608 - Accuracy: 0.7941 - F1: 0.7913
sub_24:Test (Best Model) - Loss: 1.6913 - Accuracy: 0.6176 - F1: 0.5983
sub_23:Test (Best Model) - Loss: 0.4646 - Accuracy: 0.8406 - F1: 0.8418
sub_7:Test (Best Model) - Loss: 0.5816 - Accuracy: 0.9118 - F1: 0.9040
sub_3:Test (Best Model) - Loss: 0.9160 - Accuracy: 0.7059 - F1: 0.6918
sub_10:Test (Best Model) - Loss: 2.2696 - Accuracy: 0.3971 - F1: 0.3592
sub_21:Test (Best Model) - Loss: 0.4215 - Accuracy: 0.8824 - F1: 0.8795
sub_16:Test (Best Model) - Loss: 1.6301 - Accuracy: 0.6471 - F1: 0.6482
sub_19:Test (Best Model) - Loss: 4.1806 - Accuracy: 0.4265 - F1: 0.3464
sub_26:Test (Best Model) - Loss: 0.9611 - Accuracy: 0.6957 - F1: 0.6932
sub_1:Test (Best Model) - Loss: 1.9994 - Accuracy: 0.6324 - F1: 0.6450
sub_14:Test (Best Model) - Loss: 4.2514 - Accuracy: 0.4559 - F1: 0.3693
sub_4:Test (Best Model) - Loss: 1.8046 - Accuracy: 0.6812 - F1: 0.6415
sub_18:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.7826 - F1: 0.7884
sub_27:Test (Best Model) - Loss: 1.7182 - Accuracy: 0.5797 - F1: 0.5178
sub_25:Test (Best Model) - Loss: 0.1980 - Accuracy: 0.8986 - F1: 0.8986
sub_11:Test (Best Model) - Loss: 0.8898 - Accuracy: 0.7101 - F1: 0.7094
sub_17:Test (Best Model) - Loss: 1.7182 - Accuracy: 0.5797 - F1: 0.5178
sub_29:Test (Best Model) - Loss: 3.4032 - Accuracy: 0.5294 - F1: 0.5421
sub_20:Test (Best Model) - Loss: 2.6469 - Accuracy: 0.5882 - F1: 0.5479
sub_23:Test (Best Model) - Loss: 1.9022 - Accuracy: 0.4559 - F1: 0.3505
sub_22:Test (Best Model) - Loss: 2.2448 - Accuracy: 0.5588 - F1: 0.5472
sub_8:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.7353 - F1: 0.6631
sub_6:Test (Best Model) - Loss: 2.4617 - Accuracy: 0.5588 - F1: 0.5649
sub_28:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.6324 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 1.8547 - Accuracy: 0.6377 - F1: 0.6112
sub_14:Test (Best Model) - Loss: 1.3428 - Accuracy: 0.6471 - F1: 0.6116
sub_25:Test (Best Model) - Loss: 1.8050 - Accuracy: 0.7059 - F1: 0.6618
sub_7:Test (Best Model) - Loss: 1.9206 - Accuracy: 0.6324 - F1: 0.5490
sub_24:Test (Best Model) - Loss: 0.7937 - Accuracy: 0.7500 - F1: 0.7268
sub_5:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.7794 - F1: 0.7397
sub_13:Test (Best Model) - Loss: 1.7493 - Accuracy: 0.6029 - F1: 0.5574
sub_9:Test (Best Model) - Loss: 1.3177 - Accuracy: 0.6618 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 2.1129 - Accuracy: 0.7059 - F1: 0.6443
sub_10:Test (Best Model) - Loss: 1.5018 - Accuracy: 0.6618 - F1: 0.5840
sub_1:Test (Best Model) - Loss: 2.2500 - Accuracy: 0.5882 - F1: 0.5897
sub_18:Test (Best Model) - Loss: 2.5247 - Accuracy: 0.4265 - F1: 0.4904
sub_15:Test (Best Model) - Loss: 1.5022 - Accuracy: 0.6912 - F1: 0.6821
sub_20:Test (Best Model) - Loss: 1.5597 - Accuracy: 0.7206 - F1: 0.6468
sub_26:Test (Best Model) - Loss: 1.9684 - Accuracy: 0.5441 - F1: 0.5225
sub_21:Test (Best Model) - Loss: 0.9170 - Accuracy: 0.8235 - F1: 0.8181
sub_11:Test (Best Model) - Loss: 0.9655 - Accuracy: 0.8261 - F1: 0.8185
sub_25:Test (Best Model) - Loss: 0.9913 - Accuracy: 0.6912 - F1: 0.6686
sub_4:Test (Best Model) - Loss: 0.4818 - Accuracy: 0.7681 - F1: 0.7526
sub_8:Test (Best Model) - Loss: 0.6017 - Accuracy: 0.7353 - F1: 0.6812
sub_10:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.3824 - F1: 0.3268
sub_23:Test (Best Model) - Loss: 2.2771 - Accuracy: 0.5147 - F1: 0.4479
sub_28:Test (Best Model) - Loss: 1.7147 - Accuracy: 0.3824 - F1: 0.2906
sub_3:Test (Best Model) - Loss: 1.8211 - Accuracy: 0.6522 - F1: 0.6231
sub_27:Test (Best Model) - Loss: 1.4611 - Accuracy: 0.5217 - F1: 0.4730
sub_2:Test (Best Model) - Loss: 0.7573 - Accuracy: 0.7681 - F1: 0.7709
sub_17:Test (Best Model) - Loss: 1.4611 - Accuracy: 0.5217 - F1: 0.4730
sub_14:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.4559 - F1: 0.4839
sub_19:Test (Best Model) - Loss: 1.9727 - Accuracy: 0.6912 - F1: 0.6964
sub_6:Test (Best Model) - Loss: 1.2450 - Accuracy: 0.5942 - F1: 0.5549
sub_16:Test (Best Model) - Loss: 0.8686 - Accuracy: 0.8088 - F1: 0.8035
sub_7:Test (Best Model) - Loss: 1.8146 - Accuracy: 0.6471 - F1: 0.5886
sub_29:Test (Best Model) - Loss: 0.2534 - Accuracy: 0.8824 - F1: 0.8871
sub_5:Test (Best Model) - Loss: 0.5650 - Accuracy: 0.7647 - F1: 0.7297
sub_22:Test (Best Model) - Loss: 1.7299 - Accuracy: 0.6232 - F1: 0.6370
sub_13:Test (Best Model) - Loss: 1.5171 - Accuracy: 0.4783 - F1: 0.5155
sub_20:Test (Best Model) - Loss: 0.8131 - Accuracy: 0.6912 - F1: 0.6421
sub_25:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.5882 - F1: 0.5571
sub_15:Test (Best Model) - Loss: 1.6402 - Accuracy: 0.6618 - F1: 0.6776
sub_26:Test (Best Model) - Loss: 1.2557 - Accuracy: 0.6912 - F1: 0.6879
sub_9:Test (Best Model) - Loss: 1.9102 - Accuracy: 0.5441 - F1: 0.4917
sub_4:Test (Best Model) - Loss: 0.5084 - Accuracy: 0.7536 - F1: 0.7481
sub_8:Test (Best Model) - Loss: 1.4710 - Accuracy: 0.7059 - F1: 0.6379
sub_18:Test (Best Model) - Loss: 1.9951 - Accuracy: 0.6176 - F1: 0.5918
sub_23:Test (Best Model) - Loss: 2.5735 - Accuracy: 0.4412 - F1: 0.3089
sub_11:Test (Best Model) - Loss: 1.0752 - Accuracy: 0.7391 - F1: 0.7022
sub_29:Test (Best Model) - Loss: 0.4083 - Accuracy: 0.7941 - F1: 0.7790
sub_12:Test (Best Model) - Loss: 0.7745 - Accuracy: 0.7826 - F1: 0.7785
sub_24:Test (Best Model) - Loss: 1.0107 - Accuracy: 0.7647 - F1: 0.7346
sub_19:Test (Best Model) - Loss: 1.0452 - Accuracy: 0.5735 - F1: 0.5317
sub_14:Test (Best Model) - Loss: 1.4862 - Accuracy: 0.4706 - F1: 0.4306
sub_3:Test (Best Model) - Loss: 2.1090 - Accuracy: 0.6087 - F1: 0.5872
sub_21:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.8824 - F1: 0.8818
sub_7:Test (Best Model) - Loss: 1.9065 - Accuracy: 0.6912 - F1: 0.6078
sub_10:Test (Best Model) - Loss: 1.9613 - Accuracy: 0.4412 - F1: 0.3874
sub_1:Test (Best Model) - Loss: 1.5165 - Accuracy: 0.6667 - F1: 0.6865
sub_27:Test (Best Model) - Loss: 1.2489 - Accuracy: 0.5942 - F1: 0.5642
sub_28:Test (Best Model) - Loss: 4.1947 - Accuracy: 0.4265 - F1: 0.3450
sub_17:Test (Best Model) - Loss: 1.2489 - Accuracy: 0.5942 - F1: 0.5642
sub_2:Test (Best Model) - Loss: 1.4352 - Accuracy: 0.7353 - F1: 0.7087
sub_22:Test (Best Model) - Loss: 1.7889 - Accuracy: 0.5652 - F1: 0.5001
sub_15:Test (Best Model) - Loss: 0.9611 - Accuracy: 0.6324 - F1: 0.6266
sub_13:Test (Best Model) - Loss: 1.5106 - Accuracy: 0.4203 - F1: 0.4504
sub_16:Test (Best Model) - Loss: 0.3645 - Accuracy: 0.9118 - F1: 0.9124
sub_5:Test (Best Model) - Loss: 1.2366 - Accuracy: 0.7059 - F1: 0.6384
sub_8:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.7206 - F1: 0.6360
sub_9:Test (Best Model) - Loss: 1.1797 - Accuracy: 0.6324 - F1: 0.5904
sub_25:Test (Best Model) - Loss: 1.0620 - Accuracy: 0.7794 - F1: 0.7819
sub_26:Test (Best Model) - Loss: 1.4659 - Accuracy: 0.5588 - F1: 0.5191
sub_11:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.7681 - F1: 0.7529
sub_6:Test (Best Model) - Loss: 1.7177 - Accuracy: 0.5797 - F1: 0.5211
sub_21:Test (Best Model) - Loss: 0.5349 - Accuracy: 0.7941 - F1: 0.7812
sub_18:Test (Best Model) - Loss: 1.4334 - Accuracy: 0.6029 - F1: 0.6087
sub_4:Test (Best Model) - Loss: 0.3525 - Accuracy: 0.8986 - F1: 0.9021
sub_14:Test (Best Model) - Loss: 3.4946 - Accuracy: 0.4118 - F1: 0.4242
sub_3:Test (Best Model) - Loss: 1.1719 - Accuracy: 0.6812 - F1: 0.6571
sub_23:Test (Best Model) - Loss: 2.6847 - Accuracy: 0.5294 - F1: 0.4330
sub_19:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.6176 - F1: 0.6485
sub_24:Test (Best Model) - Loss: 1.5727 - Accuracy: 0.7206 - F1: 0.6734
sub_20:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.6176 - F1: 0.5372
sub_12:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.7971 - F1: 0.8011
sub_27:Test (Best Model) - Loss: 0.8285 - Accuracy: 0.6957 - F1: 0.7000
sub_29:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.7941 - F1: 0.7833
sub_17:Test (Best Model) - Loss: 0.8285 - Accuracy: 0.6957 - F1: 0.7000
sub_1:Test (Best Model) - Loss: 1.3095 - Accuracy: 0.5652 - F1: 0.5486
sub_28:Test (Best Model) - Loss: 3.2394 - Accuracy: 0.3971 - F1: 0.3035
sub_2:Test (Best Model) - Loss: 0.9321 - Accuracy: 0.7059 - F1: 0.6630
sub_10:Test (Best Model) - Loss: 2.8736 - Accuracy: 0.3824 - F1: 0.2972
sub_22:Test (Best Model) - Loss: 1.9639 - Accuracy: 0.5072 - F1: 0.4333
sub_7:Test (Best Model) - Loss: 1.5092 - Accuracy: 0.7059 - F1: 0.6366
sub_5:Test (Best Model) - Loss: 1.4179 - Accuracy: 0.7353 - F1: 0.6564
sub_25:Test (Best Model) - Loss: 1.4406 - Accuracy: 0.7647 - F1: 0.7231
sub_9:Test (Best Model) - Loss: 1.1453 - Accuracy: 0.5000 - F1: 0.4278
sub_16:Test (Best Model) - Loss: 0.5985 - Accuracy: 0.8235 - F1: 0.8319
sub_8:Test (Best Model) - Loss: 1.1760 - Accuracy: 0.7353 - F1: 0.6572
sub_13:Test (Best Model) - Loss: 3.1095 - Accuracy: 0.4783 - F1: 0.4280
sub_18:Test (Best Model) - Loss: 1.4710 - Accuracy: 0.5147 - F1: 0.5623
sub_3:Test (Best Model) - Loss: 1.6306 - Accuracy: 0.6812 - F1: 0.6470
sub_15:Test (Best Model) - Loss: 1.4384 - Accuracy: 0.7353 - F1: 0.7299
sub_21:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.8382 - F1: 0.8351
sub_11:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.8551 - F1: 0.8538
sub_19:Test (Best Model) - Loss: 1.7033 - Accuracy: 0.6029 - F1: 0.6216
sub_23:Test (Best Model) - Loss: 2.7910 - Accuracy: 0.4853 - F1: 0.3760
sub_14:Test (Best Model) - Loss: 3.1089 - Accuracy: 0.3235 - F1: 0.3573
sub_20:Test (Best Model) - Loss: 1.7642 - Accuracy: 0.7059 - F1: 0.6431
sub_4:Test (Best Model) - Loss: 1.1808 - Accuracy: 0.7391 - F1: 0.6885
sub_24:Test (Best Model) - Loss: 1.2461 - Accuracy: 0.6765 - F1: 0.6833
sub_27:Test (Best Model) - Loss: 1.8423 - Accuracy: 0.5362 - F1: 0.5134
sub_17:Test (Best Model) - Loss: 1.8423 - Accuracy: 0.5362 - F1: 0.5134
sub_1:Test (Best Model) - Loss: 1.0560 - Accuracy: 0.6522 - F1: 0.6361
sub_6:Test (Best Model) - Loss: 1.9898 - Accuracy: 0.5797 - F1: 0.5283
sub_26:Test (Best Model) - Loss: 2.1046 - Accuracy: 0.6029 - F1: 0.6030
sub_22:Test (Best Model) - Loss: 1.5581 - Accuracy: 0.6087 - F1: 0.5454
sub_28:Test (Best Model) - Loss: 2.9655 - Accuracy: 0.4412 - F1: 0.3429
sub_12:Test (Best Model) - Loss: 0.9325 - Accuracy: 0.8406 - F1: 0.8397
sub_3:Test (Best Model) - Loss: 0.5448 - Accuracy: 0.8116 - F1: 0.8165
sub_5:Test (Best Model) - Loss: 0.8200 - Accuracy: 0.7353 - F1: 0.6777
sub_25:Test (Best Model) - Loss: 1.7936 - Accuracy: 0.7206 - F1: 0.7192
sub_16:Test (Best Model) - Loss: 0.7991 - Accuracy: 0.7500 - F1: 0.7600
sub_2:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.8235 - F1: 0.8298
sub_18:Test (Best Model) - Loss: 1.1788 - Accuracy: 0.5735 - F1: 0.5755
sub_7:Test (Best Model) - Loss: 2.4508 - Accuracy: 0.6912 - F1: 0.6189
sub_8:Test (Best Model) - Loss: 3.0250 - Accuracy: 0.6324 - F1: 0.5862
sub_9:Test (Best Model) - Loss: 1.5724 - Accuracy: 0.5588 - F1: 0.4899
sub_29:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.8235 - F1: 0.8180
sub_21:Test (Best Model) - Loss: 0.9463 - Accuracy: 0.7794 - F1: 0.7670
sub_15:Test (Best Model) - Loss: 0.8999 - Accuracy: 0.8088 - F1: 0.7947
sub_20:Test (Best Model) - Loss: 0.9672 - Accuracy: 0.7059 - F1: 0.6661
sub_13:Test (Best Model) - Loss: 2.4238 - Accuracy: 0.5507 - F1: 0.5268
sub_19:Test (Best Model) - Loss: 1.4855 - Accuracy: 0.5882 - F1: 0.6192
sub_24:Test (Best Model) - Loss: 1.0115 - Accuracy: 0.6912 - F1: 0.6509
sub_10:Test (Best Model) - Loss: 1.1106 - Accuracy: 0.4706 - F1: 0.4701
sub_11:Test (Best Model) - Loss: 0.8149 - Accuracy: 0.8406 - F1: 0.8312
sub_5:Test (Best Model) - Loss: 1.9303 - Accuracy: 0.5441 - F1: 0.4854
sub_23:Test (Best Model) - Loss: 2.9121 - Accuracy: 0.4638 - F1: 0.4135
sub_14:Test (Best Model) - Loss: 0.3340 - Accuracy: 0.8676 - F1: 0.8720
sub_17:Test (Best Model) - Loss: 1.1412 - Accuracy: 0.6471 - F1: 0.6336
sub_27:Test (Best Model) - Loss: 1.1412 - Accuracy: 0.6471 - F1: 0.6336
sub_22:Test (Best Model) - Loss: 2.2521 - Accuracy: 0.5507 - F1: 0.5365
sub_3:Test (Best Model) - Loss: 0.5798 - Accuracy: 0.8551 - F1: 0.8587
sub_28:Test (Best Model) - Loss: 4.8939 - Accuracy: 0.4412 - F1: 0.3558
sub_6:Test (Best Model) - Loss: 2.2919 - Accuracy: 0.6232 - F1: 0.5533
sub_25:Test (Best Model) - Loss: 1.8205 - Accuracy: 0.7206 - F1: 0.7185
sub_4:Test (Best Model) - Loss: 0.8801 - Accuracy: 0.7826 - F1: 0.7479
sub_12:Test (Best Model) - Loss: 1.3078 - Accuracy: 0.7536 - F1: 0.7442
sub_26:Test (Best Model) - Loss: 1.2647 - Accuracy: 0.7059 - F1: 0.6729
sub_16:Test (Best Model) - Loss: 1.1946 - Accuracy: 0.7059 - F1: 0.6934
sub_8:Test (Best Model) - Loss: 1.9704 - Accuracy: 0.6029 - F1: 0.5709
sub_1:Test (Best Model) - Loss: 1.4884 - Accuracy: 0.6812 - F1: 0.6780
sub_18:Test (Best Model) - Loss: 2.0164 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.5627 - Accuracy: 0.8676 - F1: 0.8617
sub_7:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.7794 - F1: 0.7730
sub_23:Test (Best Model) - Loss: 2.7381 - Accuracy: 0.4783 - F1: 0.4172
sub_19:Test (Best Model) - Loss: 2.2449 - Accuracy: 0.5441 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 2.5817 - Accuracy: 0.6377 - F1: 0.6303
sub_3:Test (Best Model) - Loss: 1.2355 - Accuracy: 0.7101 - F1: 0.7014
sub_2:Test (Best Model) - Loss: 1.1146 - Accuracy: 0.7500 - F1: 0.7593
sub_29:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.8382 - F1: 0.8423
sub_24:Test (Best Model) - Loss: 0.5250 - Accuracy: 0.8382 - F1: 0.8445
sub_10:Test (Best Model) - Loss: 1.6780 - Accuracy: 0.7101 - F1: 0.6787
sub_15:Test (Best Model) - Loss: 0.9525 - Accuracy: 0.7353 - F1: 0.7453
sub_14:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.7059 - F1: 0.6938
sub_5:Test (Best Model) - Loss: 2.0133 - Accuracy: 0.6471 - F1: 0.5643
sub_9:Test (Best Model) - Loss: 1.8613 - Accuracy: 0.5147 - F1: 0.4690
sub_11:Test (Best Model) - Loss: 0.5675 - Accuracy: 0.7681 - F1: 0.7689
sub_25:Test (Best Model) - Loss: 1.8187 - Accuracy: 0.7059 - F1: 0.6938
sub_27:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.7647 - F1: 0.7613
sub_13:Test (Best Model) - Loss: 1.7199 - Accuracy: 0.5217 - F1: 0.4981
sub_17:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.7647 - F1: 0.7613
sub_28:Test (Best Model) - Loss: 3.4217 - Accuracy: 0.4559 - F1: 0.3657
sub_21:Test (Best Model) - Loss: 1.4918 - Accuracy: 0.7206 - F1: 0.6474
sub_12:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.7826 - F1: 0.7908
sub_8:Test (Best Model) - Loss: 1.3954 - Accuracy: 0.6471 - F1: 0.6050
sub_7:Test (Best Model) - Loss: 1.1194 - Accuracy: 0.7206 - F1: 0.6661
sub_26:Test (Best Model) - Loss: 1.2208 - Accuracy: 0.5882 - F1: 0.5873
sub_22:Test (Best Model) - Loss: 2.2440 - Accuracy: 0.6765 - F1: 0.6628
sub_6:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.7536 - F1: 0.7478
sub_16:Test (Best Model) - Loss: 1.9433 - Accuracy: 0.6765 - F1: 0.6690
sub_18:Test (Best Model) - Loss: 2.0096 - Accuracy: 0.5294 - F1: 0.5255
sub_23:Test (Best Model) - Loss: 2.7254 - Accuracy: 0.5072 - F1: 0.4531
sub_3:Test (Best Model) - Loss: 0.7214 - Accuracy: 0.7971 - F1: 0.8073
sub_1:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.6957 - F1: 0.7114
sub_20:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.7971 - F1: 0.7975
sub_4:Test (Best Model) - Loss: 2.5581 - Accuracy: 0.6812 - F1: 0.6191
sub_15:Test (Best Model) - Loss: 2.2099 - Accuracy: 0.6618 - F1: 0.5990
sub_14:Test (Best Model) - Loss: 0.2902 - Accuracy: 0.8824 - F1: 0.8878
sub_24:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.7647 - F1: 0.7754
sub_19:Test (Best Model) - Loss: 3.2525 - Accuracy: 0.4559 - F1: 0.3865
sub_11:Test (Best Model) - Loss: 0.8816 - Accuracy: 0.7391 - F1: 0.7396
sub_25:Test (Best Model) - Loss: 1.4487 - Accuracy: 0.6618 - F1: 0.6408
sub_5:Test (Best Model) - Loss: 0.8578 - Accuracy: 0.7353 - F1: 0.6631
sub_2:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.7353 - F1: 0.7127
sub_10:Test (Best Model) - Loss: 1.7219 - Accuracy: 0.6377 - F1: 0.6056
sub_29:Test (Best Model) - Loss: 2.0611 - Accuracy: 0.6232 - F1: 0.5583
sub_27:Test (Best Model) - Loss: 1.5852 - Accuracy: 0.6029 - F1: 0.5987
sub_8:Test (Best Model) - Loss: 1.7922 - Accuracy: 0.6471 - F1: 0.6030
sub_21:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.7500 - F1: 0.6874
sub_12:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.7206 - F1: 0.7306
sub_17:Test (Best Model) - Loss: 1.5852 - Accuracy: 0.6029 - F1: 0.5987
sub_6:Test (Best Model) - Loss: 2.1607 - Accuracy: 0.6957 - F1: 0.6253
sub_7:Test (Best Model) - Loss: 1.5531 - Accuracy: 0.7059 - F1: 0.6839
sub_16:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.6912 - F1: 0.6895
sub_9:Test (Best Model) - Loss: 2.1782 - Accuracy: 0.6324 - F1: 0.5625
sub_18:Test (Best Model) - Loss: 2.6316 - Accuracy: 0.5294 - F1: 0.5097
sub_13:Test (Best Model) - Loss: 4.5992 - Accuracy: 0.4559 - F1: 0.3333
sub_28:Test (Best Model) - Loss: 3.6151 - Accuracy: 0.4706 - F1: 0.3435
sub_23:Test (Best Model) - Loss: 2.2925 - Accuracy: 0.4928 - F1: 0.4436
sub_22:Test (Best Model) - Loss: 1.7203 - Accuracy: 0.6176 - F1: 0.5831
sub_3:Test (Best Model) - Loss: 0.8646 - Accuracy: 0.7391 - F1: 0.7475
sub_26:Test (Best Model) - Loss: 1.7372 - Accuracy: 0.5441 - F1: 0.5619
sub_1:Test (Best Model) - Loss: 2.1538 - Accuracy: 0.7353 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.6912 - F1: 0.6876
sub_15:Test (Best Model) - Loss: 3.2624 - Accuracy: 0.5000 - F1: 0.3781
sub_14:Test (Best Model) - Loss: 0.3524 - Accuracy: 0.8235 - F1: 0.8295
sub_24:Test (Best Model) - Loss: 0.8746 - Accuracy: 0.7647 - F1: 0.7442
sub_10:Test (Best Model) - Loss: 0.7375 - Accuracy: 0.7536 - F1: 0.7430
sub_11:Test (Best Model) - Loss: 0.8610 - Accuracy: 0.7971 - F1: 0.7783
sub_4:Test (Best Model) - Loss: 1.4084 - Accuracy: 0.7101 - F1: 0.6439
sub_9:Test (Best Model) - Loss: 1.1384 - Accuracy: 0.6765 - F1: 0.6595
sub_5:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.7353 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 1.1002 - Accuracy: 0.7391 - F1: 0.7393
sub_19:Test (Best Model) - Loss: 1.4357 - Accuracy: 0.5882 - F1: 0.5555
sub_29:Test (Best Model) - Loss: 2.3666 - Accuracy: 0.6812 - F1: 0.6179
sub_7:Test (Best Model) - Loss: 0.7175 - Accuracy: 0.7353 - F1: 0.7248
sub_16:Test (Best Model) - Loss: 1.2759 - Accuracy: 0.5147 - F1: 0.5078
sub_6:Test (Best Model) - Loss: 1.4469 - Accuracy: 0.7101 - F1: 0.6793
sub_2:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.7971 - F1: 0.8070
sub_27:Test (Best Model) - Loss: 1.0346 - Accuracy: 0.7059 - F1: 0.7060
sub_21:Test (Best Model) - Loss: 1.1689 - Accuracy: 0.7500 - F1: 0.6965
sub_12:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.6618 - F1: 0.6347
sub_17:Test (Best Model) - Loss: 1.0346 - Accuracy: 0.7059 - F1: 0.7060
sub_8:Test (Best Model) - Loss: 2.2064 - Accuracy: 0.6176 - F1: 0.5856
sub_23:Test (Best Model) - Loss: 3.0294 - Accuracy: 0.5362 - F1: 0.4726
sub_13:Test (Best Model) - Loss: 3.3224 - Accuracy: 0.4412 - F1: 0.3072
sub_22:Test (Best Model) - Loss: 1.0755 - Accuracy: 0.7059 - F1: 0.6925
sub_1:Test (Best Model) - Loss: 2.3225 - Accuracy: 0.6912 - F1: 0.6353
sub_11:Test (Best Model) - Loss: 0.7498 - Accuracy: 0.7971 - F1: 0.7946
sub_28:Test (Best Model) - Loss: 3.5023 - Accuracy: 0.4706 - F1: 0.3415
sub_9:Test (Best Model) - Loss: 1.0890 - Accuracy: 0.7059 - F1: 0.6741
sub_5:Test (Best Model) - Loss: 1.7827 - Accuracy: 0.7353 - F1: 0.6518
sub_18:Test (Best Model) - Loss: 4.0034 - Accuracy: 0.5147 - F1: 0.4878
sub_24:Test (Best Model) - Loss: 0.8935 - Accuracy: 0.6765 - F1: 0.6938
sub_15:Test (Best Model) - Loss: 3.2617 - Accuracy: 0.5441 - F1: 0.4499
sub_10:Test (Best Model) - Loss: 1.2942 - Accuracy: 0.6957 - F1: 0.6623
sub_14:Test (Best Model) - Loss: 1.1213 - Accuracy: 0.7059 - F1: 0.6465
sub_16:Test (Best Model) - Loss: 0.7471 - Accuracy: 0.7353 - F1: 0.7384
sub_4:Test (Best Model) - Loss: 0.7565 - Accuracy: 0.7391 - F1: 0.6667
sub_29:Test (Best Model) - Loss: 1.9197 - Accuracy: 0.6087 - F1: 0.5748
sub_20:Test (Best Model) - Loss: 1.6486 - Accuracy: 0.6957 - F1: 0.6885
sub_7:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.6471 - F1: 0.5918
sub_6:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.7246 - F1: 0.6966
sub_26:Test (Best Model) - Loss: 2.5158 - Accuracy: 0.5441 - F1: 0.5668
sub_19:Test (Best Model) - Loss: 1.7928 - Accuracy: 0.5000 - F1: 0.4859
sub_21:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.7353 - F1: 0.6721
sub_9:Test (Best Model) - Loss: 1.2066 - Accuracy: 0.5147 - F1: 0.4624
sub_27:Test (Best Model) - Loss: 1.1117 - Accuracy: 0.6912 - F1: 0.6540
sub_1:Test (Best Model) - Loss: 1.2065 - Accuracy: 0.7647 - F1: 0.7343
sub_12:Test (Best Model) - Loss: 1.1787 - Accuracy: 0.7059 - F1: 0.6827
sub_17:Test (Best Model) - Loss: 1.1117 - Accuracy: 0.6912 - F1: 0.6540
sub_2:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.6377 - F1: 0.6386
sub_28:Test (Best Model) - Loss: 1.9826 - Accuracy: 0.3676 - F1: 0.3035
sub_11:Test (Best Model) - Loss: 0.8893 - Accuracy: 0.6522 - F1: 0.6356
sub_18:Test (Best Model) - Loss: 2.3610 - Accuracy: 0.5294 - F1: 0.5067
sub_24:Test (Best Model) - Loss: 0.3231 - Accuracy: 0.8088 - F1: 0.8094
sub_20:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.7536 - F1: 0.7530
sub_10:Test (Best Model) - Loss: 1.0257 - Accuracy: 0.7246 - F1: 0.6590
sub_22:Test (Best Model) - Loss: 1.1683 - Accuracy: 0.7500 - F1: 0.7287
sub_29:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.6812 - F1: 0.6215
sub_26:Test (Best Model) - Loss: 0.8801 - Accuracy: 0.7059 - F1: 0.7186
sub_4:Test (Best Model) - Loss: 1.0399 - Accuracy: 0.7101 - F1: 0.6452
sub_16:Test (Best Model) - Loss: 1.0244 - Accuracy: 0.6324 - F1: 0.6338
sub_13:Test (Best Model) - Loss: 3.5872 - Accuracy: 0.5441 - F1: 0.4996
sub_15:Test (Best Model) - Loss: 2.3554 - Accuracy: 0.5588 - F1: 0.4766
sub_19:Test (Best Model) - Loss: 2.8396 - Accuracy: 0.4412 - F1: 0.3683
sub_6:Test (Best Model) - Loss: 2.0147 - Accuracy: 0.6957 - F1: 0.6285
sub_9:Test (Best Model) - Loss: 1.5671 - Accuracy: 0.6765 - F1: 0.6830
sub_1:Test (Best Model) - Loss: 1.5480 - Accuracy: 0.7206 - F1: 0.6509
sub_12:Test (Best Model) - Loss: 0.7832 - Accuracy: 0.7647 - F1: 0.7586
sub_4:Test (Best Model) - Loss: 0.7497 - Accuracy: 0.7246 - F1: 0.6595
sub_2:Test (Best Model) - Loss: 2.0577 - Accuracy: 0.6232 - F1: 0.5925
sub_26:Test (Best Model) - Loss: 1.4099 - Accuracy: 0.4853 - F1: 0.5015
sub_22:Test (Best Model) - Loss: 1.9558 - Accuracy: 0.6912 - F1: 0.6690
sub_29:Test (Best Model) - Loss: 1.7395 - Accuracy: 0.6522 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 2.5555 - Accuracy: 0.6324 - F1: 0.5559
sub_13:Test (Best Model) - Loss: 3.6682 - Accuracy: 0.4559 - F1: 0.3401
sub_28:Test (Best Model) - Loss: 3.9077 - Accuracy: 0.4265 - F1: 0.3825
sub_6:Test (Best Model) - Loss: 2.0292 - Accuracy: 0.6812 - F1: 0.6076
sub_1:Test (Best Model) - Loss: 1.9045 - Accuracy: 0.7206 - F1: 0.6415
sub_12:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.8088 - F1: 0.8037
sub_2:Test (Best Model) - Loss: 1.0903 - Accuracy: 0.6522 - F1: 0.6455
sub_13:Test (Best Model) - Loss: 3.1181 - Accuracy: 0.5882 - F1: 0.5348
sub_28:Test (Best Model) - Loss: 2.9373 - Accuracy: 0.4412 - F1: 0.3769
sub_2:Test (Best Model) - Loss: 1.2496 - Accuracy: 0.7101 - F1: 0.7125

=== Summary Results ===

acc: 66.29 ± 8.60
F1: 63.57 ± 9.67
acc-in: 95.47 ± 2.21
F1-in: 95.36 ± 2.34
