lr: 0.0001
sub_8:Test (Best Model) - Loss: 1.9517 - Accuracy: 0.6765 - F1: 0.6012
sub_6:Test (Best Model) - Loss: 1.7748 - Accuracy: 0.5441 - F1: 0.4950
sub_12:Test (Best Model) - Loss: 0.9942 - Accuracy: 0.6765 - F1: 0.6728
sub_16:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.7941 - F1: 0.7999
sub_13:Test (Best Model) - Loss: 1.8044 - Accuracy: 0.5588 - F1: 0.5060
sub_19:Test (Best Model) - Loss: 3.4032 - Accuracy: 0.4265 - F1: 0.3436
sub_27:Test (Best Model) - Loss: 0.1783 - Accuracy: 0.9565 - F1: 0.9561
sub_22:Test (Best Model) - Loss: 2.2102 - Accuracy: 0.4706 - F1: 0.4107
sub_5:Test (Best Model) - Loss: 2.4643 - Accuracy: 0.5000 - F1: 0.4286
sub_4:Test (Best Model) - Loss: 1.0101 - Accuracy: 0.7101 - F1: 0.6618
sub_9:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.6912 - F1: 0.6914
sub_17:Test (Best Model) - Loss: 0.1783 - Accuracy: 0.9565 - F1: 0.9561
sub_24:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.7059 - F1: 0.6827
sub_7:Test (Best Model) - Loss: 0.2501 - Accuracy: 0.8971 - F1: 0.8929
sub_21:Test (Best Model) - Loss: 0.3154 - Accuracy: 0.8971 - F1: 0.8892
sub_10:Test (Best Model) - Loss: 3.1357 - Accuracy: 0.4118 - F1: 0.4745
sub_14:Test (Best Model) - Loss: 3.4627 - Accuracy: 0.4853 - F1: 0.4049
sub_18:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.7536 - F1: 0.7654
sub_28:Test (Best Model) - Loss: 2.1724 - Accuracy: 0.4412 - F1: 0.3869
sub_23:Test (Best Model) - Loss: 0.4775 - Accuracy: 0.8406 - F1: 0.8512
sub_29:Test (Best Model) - Loss: 2.0697 - Accuracy: 0.5294 - F1: 0.5534
sub_15:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.7794 - F1: 0.7950
sub_3:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.8235 - F1: 0.8282
sub_11:Test (Best Model) - Loss: 1.2433 - Accuracy: 0.7246 - F1: 0.6519
sub_26:Test (Best Model) - Loss: 2.0672 - Accuracy: 0.6377 - F1: 0.6214
sub_2:Test (Best Model) - Loss: 1.6521 - Accuracy: 0.6522 - F1: 0.6364
sub_20:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.7353 - F1: 0.6858
sub_8:Test (Best Model) - Loss: 2.1748 - Accuracy: 0.6765 - F1: 0.6132
sub_25:Test (Best Model) - Loss: 0.1738 - Accuracy: 0.9710 - F1: 0.9686
sub_5:Test (Best Model) - Loss: 1.8729 - Accuracy: 0.7353 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 3.0157 - Accuracy: 0.5294 - F1: 0.5191
sub_6:Test (Best Model) - Loss: 2.6464 - Accuracy: 0.4559 - F1: 0.3862
sub_16:Test (Best Model) - Loss: 1.8576 - Accuracy: 0.5735 - F1: 0.5510
sub_18:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.7391 - F1: 0.7484
sub_22:Test (Best Model) - Loss: 3.2450 - Accuracy: 0.3824 - F1: 0.3664
sub_12:Test (Best Model) - Loss: 0.9917 - Accuracy: 0.7500 - F1: 0.7102
sub_24:Test (Best Model) - Loss: 2.2002 - Accuracy: 0.5294 - F1: 0.4492
sub_4:Test (Best Model) - Loss: 2.1336 - Accuracy: 0.6957 - F1: 0.6307
sub_7:Test (Best Model) - Loss: 0.0804 - Accuracy: 0.9706 - F1: 0.9676
sub_10:Test (Best Model) - Loss: 2.5591 - Accuracy: 0.4559 - F1: 0.4854
sub_9:Test (Best Model) - Loss: 1.5342 - Accuracy: 0.6324 - F1: 0.6415
sub_21:Test (Best Model) - Loss: 0.5842 - Accuracy: 0.7941 - F1: 0.8005
sub_29:Test (Best Model) - Loss: 1.0195 - Accuracy: 0.6765 - F1: 0.6798
sub_26:Test (Best Model) - Loss: 1.1751 - Accuracy: 0.6232 - F1: 0.6337
sub_19:Test (Best Model) - Loss: 4.7730 - Accuracy: 0.3676 - F1: 0.3346
sub_14:Test (Best Model) - Loss: 3.1577 - Accuracy: 0.4706 - F1: 0.3750
sub_8:Test (Best Model) - Loss: 1.7047 - Accuracy: 0.6176 - F1: 0.5851
sub_27:Test (Best Model) - Loss: 0.8505 - Accuracy: 0.8116 - F1: 0.8166
sub_11:Test (Best Model) - Loss: 1.3954 - Accuracy: 0.7101 - F1: 0.6281
sub_25:Test (Best Model) - Loss: 0.0941 - Accuracy: 0.9710 - F1: 0.9686
sub_13:Test (Best Model) - Loss: 1.4032 - Accuracy: 0.5735 - F1: 0.5237
sub_3:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.8382 - F1: 0.8377
sub_17:Test (Best Model) - Loss: 0.8505 - Accuracy: 0.8116 - F1: 0.8166
sub_28:Test (Best Model) - Loss: 1.5308 - Accuracy: 0.5882 - F1: 0.5074
sub_20:Test (Best Model) - Loss: 1.2404 - Accuracy: 0.6765 - F1: 0.6312
sub_16:Test (Best Model) - Loss: 1.6021 - Accuracy: 0.6912 - F1: 0.6403
sub_5:Test (Best Model) - Loss: 2.7346 - Accuracy: 0.7206 - F1: 0.6518
sub_4:Test (Best Model) - Loss: 1.0347 - Accuracy: 0.6812 - F1: 0.6150
sub_6:Test (Best Model) - Loss: 3.2361 - Accuracy: 0.4559 - F1: 0.3808
sub_15:Test (Best Model) - Loss: 0.8496 - Accuracy: 0.7941 - F1: 0.8065
sub_23:Test (Best Model) - Loss: 1.2075 - Accuracy: 0.7826 - F1: 0.7602
sub_9:Test (Best Model) - Loss: 0.4247 - Accuracy: 0.7941 - F1: 0.7963
sub_1:Test (Best Model) - Loss: 1.7846 - Accuracy: 0.6176 - F1: 0.6185
sub_18:Test (Best Model) - Loss: 0.7677 - Accuracy: 0.7826 - F1: 0.7735
sub_2:Test (Best Model) - Loss: 1.5331 - Accuracy: 0.6522 - F1: 0.6460
sub_12:Test (Best Model) - Loss: 1.0607 - Accuracy: 0.6765 - F1: 0.6245
sub_7:Test (Best Model) - Loss: 1.0083 - Accuracy: 0.7500 - F1: 0.6984
sub_24:Test (Best Model) - Loss: 1.5256 - Accuracy: 0.6471 - F1: 0.6368
sub_21:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.8676 - F1: 0.8715
sub_26:Test (Best Model) - Loss: 1.3420 - Accuracy: 0.5797 - F1: 0.5259
sub_22:Test (Best Model) - Loss: 3.1426 - Accuracy: 0.5147 - F1: 0.4340
sub_10:Test (Best Model) - Loss: 2.4466 - Accuracy: 0.4853 - F1: 0.5012
sub_29:Test (Best Model) - Loss: 1.8507 - Accuracy: 0.5588 - F1: 0.5711
sub_11:Test (Best Model) - Loss: 0.7778 - Accuracy: 0.7681 - F1: 0.7292
sub_25:Test (Best Model) - Loss: 0.1215 - Accuracy: 0.9710 - F1: 0.9686
sub_14:Test (Best Model) - Loss: 3.8090 - Accuracy: 0.4706 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 1.5139 - Accuracy: 0.7206 - F1: 0.6565
sub_8:Test (Best Model) - Loss: 1.8347 - Accuracy: 0.6618 - F1: 0.5979
sub_4:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.6812 - F1: 0.6354
sub_19:Test (Best Model) - Loss: 4.3027 - Accuracy: 0.3971 - F1: 0.3470
sub_16:Test (Best Model) - Loss: 0.5811 - Accuracy: 0.7941 - F1: 0.7961
sub_3:Test (Best Model) - Loss: 0.3323 - Accuracy: 0.9265 - F1: 0.9280
sub_9:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7941 - F1: 0.7833
sub_13:Test (Best Model) - Loss: 3.2625 - Accuracy: 0.4853 - F1: 0.4031
sub_20:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.5147 - F1: 0.4754
sub_27:Test (Best Model) - Loss: 0.4815 - Accuracy: 0.8551 - F1: 0.8560
sub_28:Test (Best Model) - Loss: 2.0000 - Accuracy: 0.7206 - F1: 0.6304
sub_23:Test (Best Model) - Loss: 0.9006 - Accuracy: 0.8261 - F1: 0.8050
sub_6:Test (Best Model) - Loss: 2.5531 - Accuracy: 0.4706 - F1: 0.4282
sub_18:Test (Best Model) - Loss: 0.5020 - Accuracy: 0.8261 - F1: 0.8317
sub_12:Test (Best Model) - Loss: 1.3177 - Accuracy: 0.6618 - F1: 0.5946
sub_26:Test (Best Model) - Loss: 0.8670 - Accuracy: 0.7101 - F1: 0.7221
sub_5:Test (Best Model) - Loss: 1.7830 - Accuracy: 0.7353 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.5147 - F1: 0.5588
sub_17:Test (Best Model) - Loss: 0.4815 - Accuracy: 0.8551 - F1: 0.8560
sub_7:Test (Best Model) - Loss: 0.1570 - Accuracy: 0.9265 - F1: 0.9199
sub_2:Test (Best Model) - Loss: 2.0582 - Accuracy: 0.5942 - F1: 0.5373
sub_19:Test (Best Model) - Loss: 4.1886 - Accuracy: 0.4559 - F1: 0.3697
sub_1:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.6324 - F1: 0.6332
sub_21:Test (Best Model) - Loss: 0.9433 - Accuracy: 0.7941 - F1: 0.7753
sub_24:Test (Best Model) - Loss: 1.8695 - Accuracy: 0.6471 - F1: 0.6091
sub_11:Test (Best Model) - Loss: 0.9306 - Accuracy: 0.7391 - F1: 0.7042
sub_15:Test (Best Model) - Loss: 1.0417 - Accuracy: 0.7353 - F1: 0.7498
sub_29:Test (Best Model) - Loss: 1.7231 - Accuracy: 0.6029 - F1: 0.6204
sub_22:Test (Best Model) - Loss: 2.3217 - Accuracy: 0.5735 - F1: 0.5425
sub_25:Test (Best Model) - Loss: 0.1190 - Accuracy: 0.9420 - F1: 0.9423
sub_3:Test (Best Model) - Loss: 0.4895 - Accuracy: 0.8529 - F1: 0.8552
sub_16:Test (Best Model) - Loss: 1.3080 - Accuracy: 0.6765 - F1: 0.6740
sub_6:Test (Best Model) - Loss: 1.6446 - Accuracy: 0.6471 - F1: 0.5781
sub_8:Test (Best Model) - Loss: 3.0699 - Accuracy: 0.5588 - F1: 0.5366
sub_26:Test (Best Model) - Loss: 0.8224 - Accuracy: 0.7246 - F1: 0.7296
sub_14:Test (Best Model) - Loss: 4.2018 - Accuracy: 0.4559 - F1: 0.3611
sub_27:Test (Best Model) - Loss: 0.1823 - Accuracy: 0.9420 - F1: 0.9442
sub_18:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.8696 - F1: 0.8695
sub_4:Test (Best Model) - Loss: 2.1400 - Accuracy: 0.7101 - F1: 0.6571
sub_13:Test (Best Model) - Loss: 1.1121 - Accuracy: 0.5735 - F1: 0.5223
sub_20:Test (Best Model) - Loss: 1.4314 - Accuracy: 0.5735 - F1: 0.5440
sub_11:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.7681 - F1: 0.7590
sub_19:Test (Best Model) - Loss: 4.3143 - Accuracy: 0.3971 - F1: 0.3364
sub_17:Test (Best Model) - Loss: 0.1823 - Accuracy: 0.9420 - F1: 0.9442
sub_9:Test (Best Model) - Loss: 1.4273 - Accuracy: 0.6912 - F1: 0.6878
sub_12:Test (Best Model) - Loss: 1.4136 - Accuracy: 0.6912 - F1: 0.6280
sub_2:Test (Best Model) - Loss: 1.4804 - Accuracy: 0.6812 - F1: 0.6500
sub_3:Test (Best Model) - Loss: 0.4941 - Accuracy: 0.8529 - F1: 0.8566
sub_5:Test (Best Model) - Loss: 0.5299 - Accuracy: 0.7500 - F1: 0.6861
sub_23:Test (Best Model) - Loss: 1.0225 - Accuracy: 0.7391 - F1: 0.7263
sub_6:Test (Best Model) - Loss: 0.9837 - Accuracy: 0.6232 - F1: 0.5841
sub_24:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.6618 - F1: 0.6312
sub_7:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.8529 - F1: 0.8431
sub_28:Test (Best Model) - Loss: 1.5170 - Accuracy: 0.6912 - F1: 0.6197
sub_15:Test (Best Model) - Loss: 0.3630 - Accuracy: 0.9265 - F1: 0.9279
sub_16:Test (Best Model) - Loss: 0.5855 - Accuracy: 0.8382 - F1: 0.8373
sub_29:Test (Best Model) - Loss: 1.9115 - Accuracy: 0.4706 - F1: 0.5147
sub_1:Test (Best Model) - Loss: 1.8312 - Accuracy: 0.6618 - F1: 0.6612
sub_22:Test (Best Model) - Loss: 3.5582 - Accuracy: 0.4853 - F1: 0.4369
sub_25:Test (Best Model) - Loss: 0.2273 - Accuracy: 0.9565 - F1: 0.9551
sub_10:Test (Best Model) - Loss: 1.7290 - Accuracy: 0.4118 - F1: 0.3965
sub_19:Test (Best Model) - Loss: 1.1025 - Accuracy: 0.6324 - F1: 0.6231
sub_14:Test (Best Model) - Loss: 4.1710 - Accuracy: 0.4706 - F1: 0.3750
sub_26:Test (Best Model) - Loss: 2.7523 - Accuracy: 0.5000 - F1: 0.4412
sub_18:Test (Best Model) - Loss: 2.0513 - Accuracy: 0.5588 - F1: 0.5795
sub_27:Test (Best Model) - Loss: 0.3140 - Accuracy: 0.8986 - F1: 0.8993
sub_17:Test (Best Model) - Loss: 0.3140 - Accuracy: 0.8986 - F1: 0.8993
sub_8:Test (Best Model) - Loss: 2.0842 - Accuracy: 0.7206 - F1: 0.6485
sub_4:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.8841 - F1: 0.8811
sub_20:Test (Best Model) - Loss: 1.7946 - Accuracy: 0.5588 - F1: 0.5148
sub_11:Test (Best Model) - Loss: 1.2855 - Accuracy: 0.7971 - F1: 0.7686
sub_3:Test (Best Model) - Loss: 2.3246 - Accuracy: 0.6522 - F1: 0.6085
sub_21:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.8676 - F1: 0.8676
sub_5:Test (Best Model) - Loss: 0.2992 - Accuracy: 0.8676 - F1: 0.8643
sub_7:Test (Best Model) - Loss: 1.7394 - Accuracy: 0.7353 - F1: 0.6508
sub_13:Test (Best Model) - Loss: 4.0196 - Accuracy: 0.4706 - F1: 0.4058
sub_9:Test (Best Model) - Loss: 2.2624 - Accuracy: 0.6912 - F1: 0.6230
sub_2:Test (Best Model) - Loss: 1.2672 - Accuracy: 0.7536 - F1: 0.7300
sub_6:Test (Best Model) - Loss: 1.1217 - Accuracy: 0.5797 - F1: 0.5007
sub_22:Test (Best Model) - Loss: 1.7921 - Accuracy: 0.6087 - F1: 0.5450
sub_25:Test (Best Model) - Loss: 1.8436 - Accuracy: 0.6765 - F1: 0.6064
sub_16:Test (Best Model) - Loss: 0.5318 - Accuracy: 0.7941 - F1: 0.7900
sub_15:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.8088 - F1: 0.8210
sub_12:Test (Best Model) - Loss: 1.1306 - Accuracy: 0.7391 - F1: 0.7453
sub_23:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.8551 - F1: 0.8495
sub_19:Test (Best Model) - Loss: 1.0800 - Accuracy: 0.5294 - F1: 0.4482
sub_20:Test (Best Model) - Loss: 0.9762 - Accuracy: 0.7206 - F1: 0.6495
sub_24:Test (Best Model) - Loss: 2.0762 - Accuracy: 0.7353 - F1: 0.6532
sub_10:Test (Best Model) - Loss: 2.2788 - Accuracy: 0.6912 - F1: 0.6122
sub_18:Test (Best Model) - Loss: 1.6427 - Accuracy: 0.5588 - F1: 0.5282
sub_28:Test (Best Model) - Loss: 1.6483 - Accuracy: 0.4706 - F1: 0.3730
sub_26:Test (Best Model) - Loss: 2.4909 - Accuracy: 0.3676 - F1: 0.3495
sub_14:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.6029 - F1: 0.6344
sub_4:Test (Best Model) - Loss: 0.3538 - Accuracy: 0.8696 - F1: 0.8722
sub_8:Test (Best Model) - Loss: 1.0017 - Accuracy: 0.7353 - F1: 0.6812
sub_3:Test (Best Model) - Loss: 1.6574 - Accuracy: 0.6522 - F1: 0.6167
sub_11:Test (Best Model) - Loss: 0.9674 - Accuracy: 0.7536 - F1: 0.7281
sub_27:Test (Best Model) - Loss: 1.9332 - Accuracy: 0.6087 - F1: 0.5536
sub_7:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.7059 - F1: 0.6410
sub_17:Test (Best Model) - Loss: 1.9332 - Accuracy: 0.6087 - F1: 0.5536
sub_1:Test (Best Model) - Loss: 2.6964 - Accuracy: 0.6029 - F1: 0.6055
sub_21:Test (Best Model) - Loss: 0.9939 - Accuracy: 0.7647 - F1: 0.7431
sub_6:Test (Best Model) - Loss: 0.9529 - Accuracy: 0.5797 - F1: 0.5499
sub_5:Test (Best Model) - Loss: 0.8384 - Accuracy: 0.7206 - F1: 0.6509
sub_29:Test (Best Model) - Loss: 0.6254 - Accuracy: 0.8676 - F1: 0.8714
sub_2:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.7353 - F1: 0.6942
sub_9:Test (Best Model) - Loss: 1.0636 - Accuracy: 0.7206 - F1: 0.6644
sub_10:Test (Best Model) - Loss: 0.9001 - Accuracy: 0.6471 - F1: 0.6037
sub_25:Test (Best Model) - Loss: 0.8719 - Accuracy: 0.7794 - F1: 0.7724
sub_22:Test (Best Model) - Loss: 2.1152 - Accuracy: 0.5217 - F1: 0.4615
sub_19:Test (Best Model) - Loss: 1.0549 - Accuracy: 0.6912 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 0.5075 - Accuracy: 0.7971 - F1: 0.7970
sub_16:Test (Best Model) - Loss: 0.8020 - Accuracy: 0.7794 - F1: 0.7840
sub_6:Test (Best Model) - Loss: 0.5378 - Accuracy: 0.7536 - F1: 0.7304
sub_26:Test (Best Model) - Loss: 1.9649 - Accuracy: 0.5000 - F1: 0.4388
sub_20:Test (Best Model) - Loss: 1.2245 - Accuracy: 0.6912 - F1: 0.6207
sub_13:Test (Best Model) - Loss: 1.5435 - Accuracy: 0.5362 - F1: 0.5354
sub_28:Test (Best Model) - Loss: 3.7728 - Accuracy: 0.4265 - F1: 0.3323
sub_18:Test (Best Model) - Loss: 2.5367 - Accuracy: 0.5735 - F1: 0.5887
sub_8:Test (Best Model) - Loss: 1.9152 - Accuracy: 0.7206 - F1: 0.6495
sub_14:Test (Best Model) - Loss: 0.9639 - Accuracy: 0.4412 - F1: 0.4827
sub_9:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.6912 - F1: 0.6355
sub_15:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.8088 - F1: 0.8077
sub_2:Test (Best Model) - Loss: 0.5230 - Accuracy: 0.7647 - F1: 0.7705
sub_11:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.7536 - F1: 0.7258
sub_7:Test (Best Model) - Loss: 2.0274 - Accuracy: 0.6765 - F1: 0.5952
sub_23:Test (Best Model) - Loss: 2.9914 - Accuracy: 0.4706 - F1: 0.3937
sub_21:Test (Best Model) - Loss: 0.2705 - Accuracy: 0.8824 - F1: 0.8732
sub_4:Test (Best Model) - Loss: 0.4444 - Accuracy: 0.8696 - F1: 0.8667
sub_3:Test (Best Model) - Loss: 2.3763 - Accuracy: 0.6377 - F1: 0.6033
sub_5:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.7500 - F1: 0.6930
sub_25:Test (Best Model) - Loss: 1.1539 - Accuracy: 0.6471 - F1: 0.6198
sub_10:Test (Best Model) - Loss: 1.1969 - Accuracy: 0.5294 - F1: 0.4882
sub_29:Test (Best Model) - Loss: 0.1953 - Accuracy: 0.9118 - F1: 0.9140
sub_17:Test (Best Model) - Loss: 2.2543 - Accuracy: 0.5652 - F1: 0.5197
sub_27:Test (Best Model) - Loss: 2.2543 - Accuracy: 0.5652 - F1: 0.5197
sub_24:Test (Best Model) - Loss: 2.1163 - Accuracy: 0.7353 - F1: 0.6532
sub_22:Test (Best Model) - Loss: 2.1484 - Accuracy: 0.4783 - F1: 0.4182
sub_16:Test (Best Model) - Loss: 0.7708 - Accuracy: 0.7206 - F1: 0.7194
sub_26:Test (Best Model) - Loss: 1.5796 - Accuracy: 0.5000 - F1: 0.4898
sub_7:Test (Best Model) - Loss: 1.4208 - Accuracy: 0.7353 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 0.4653 - Accuracy: 0.8696 - F1: 0.8765
sub_12:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.8261 - F1: 0.8288
sub_4:Test (Best Model) - Loss: 0.2956 - Accuracy: 0.8986 - F1: 0.9009
sub_8:Test (Best Model) - Loss: 0.7727 - Accuracy: 0.7206 - F1: 0.6476
sub_13:Test (Best Model) - Loss: 1.0771 - Accuracy: 0.4638 - F1: 0.4618
sub_10:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.7206 - F1: 0.7327
sub_19:Test (Best Model) - Loss: 2.3543 - Accuracy: 0.6176 - F1: 0.6023
sub_6:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.7971 - F1: 0.7977
sub_18:Test (Best Model) - Loss: 2.2119 - Accuracy: 0.6618 - F1: 0.6201
sub_20:Test (Best Model) - Loss: 2.0956 - Accuracy: 0.6912 - F1: 0.6167
sub_14:Test (Best Model) - Loss: 1.9339 - Accuracy: 0.3676 - F1: 0.3631
sub_28:Test (Best Model) - Loss: 3.8937 - Accuracy: 0.4265 - F1: 0.3450
sub_9:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.5735 - F1: 0.4939
sub_23:Test (Best Model) - Loss: 1.7771 - Accuracy: 0.5000 - F1: 0.4569
sub_2:Test (Best Model) - Loss: 1.0867 - Accuracy: 0.7647 - F1: 0.7453
sub_15:Test (Best Model) - Loss: 0.8837 - Accuracy: 0.7353 - F1: 0.7286
sub_5:Test (Best Model) - Loss: 0.5638 - Accuracy: 0.8235 - F1: 0.8228
sub_3:Test (Best Model) - Loss: 2.3113 - Accuracy: 0.6667 - F1: 0.6148
sub_29:Test (Best Model) - Loss: 0.2527 - Accuracy: 0.8824 - F1: 0.8848
sub_11:Test (Best Model) - Loss: 0.7608 - Accuracy: 0.7971 - F1: 0.7837
sub_25:Test (Best Model) - Loss: 0.9431 - Accuracy: 0.8088 - F1: 0.8124
sub_19:Test (Best Model) - Loss: 0.7455 - Accuracy: 0.7353 - F1: 0.7555
sub_24:Test (Best Model) - Loss: 2.2495 - Accuracy: 0.7206 - F1: 0.6402
sub_26:Test (Best Model) - Loss: 1.8302 - Accuracy: 0.6324 - F1: 0.5790
sub_7:Test (Best Model) - Loss: 1.9010 - Accuracy: 0.7353 - F1: 0.6631
sub_21:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.8088 - F1: 0.7965
sub_16:Test (Best Model) - Loss: 2.3166 - Accuracy: 0.5588 - F1: 0.5048
sub_1:Test (Best Model) - Loss: 0.7703 - Accuracy: 0.6957 - F1: 0.6816
sub_10:Test (Best Model) - Loss: 0.9798 - Accuracy: 0.6176 - F1: 0.6377
sub_22:Test (Best Model) - Loss: 1.8447 - Accuracy: 0.6087 - F1: 0.5543
sub_27:Test (Best Model) - Loss: 1.4586 - Accuracy: 0.5942 - F1: 0.5443
sub_17:Test (Best Model) - Loss: 1.4586 - Accuracy: 0.5942 - F1: 0.5443
sub_13:Test (Best Model) - Loss: 1.6019 - Accuracy: 0.6232 - F1: 0.5691
sub_18:Test (Best Model) - Loss: 1.1452 - Accuracy: 0.6176 - F1: 0.6254
sub_6:Test (Best Model) - Loss: 1.7596 - Accuracy: 0.6812 - F1: 0.6060
sub_4:Test (Best Model) - Loss: 0.5164 - Accuracy: 0.8696 - F1: 0.8647
sub_28:Test (Best Model) - Loss: 2.8604 - Accuracy: 0.4412 - F1: 0.3373
sub_3:Test (Best Model) - Loss: 1.5099 - Accuracy: 0.6377 - F1: 0.6023
sub_20:Test (Best Model) - Loss: 1.5859 - Accuracy: 0.7059 - F1: 0.6473
sub_9:Test (Best Model) - Loss: 1.0286 - Accuracy: 0.6471 - F1: 0.6123
sub_8:Test (Best Model) - Loss: 0.9333 - Accuracy: 0.6765 - F1: 0.6385
sub_12:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.7391 - F1: 0.7509
sub_29:Test (Best Model) - Loss: 0.3470 - Accuracy: 0.7941 - F1: 0.7783
sub_25:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.7353 - F1: 0.6804
sub_14:Test (Best Model) - Loss: 1.8287 - Accuracy: 0.4265 - F1: 0.4888
sub_2:Test (Best Model) - Loss: 1.6254 - Accuracy: 0.6765 - F1: 0.6248
sub_19:Test (Best Model) - Loss: 2.2372 - Accuracy: 0.5588 - F1: 0.4884
sub_11:Test (Best Model) - Loss: 0.9232 - Accuracy: 0.7826 - F1: 0.7493
sub_5:Test (Best Model) - Loss: 2.2974 - Accuracy: 0.7353 - F1: 0.6631
sub_6:Test (Best Model) - Loss: 1.0243 - Accuracy: 0.6812 - F1: 0.6077
sub_7:Test (Best Model) - Loss: 0.7546 - Accuracy: 0.7059 - F1: 0.7058
sub_21:Test (Best Model) - Loss: 0.5392 - Accuracy: 0.7500 - F1: 0.7277
sub_10:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.6957 - F1: 0.6587
sub_15:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.7941 - F1: 0.7899
sub_23:Test (Best Model) - Loss: 2.7142 - Accuracy: 0.5000 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 1.1736 - Accuracy: 0.7500 - F1: 0.7109
sub_3:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.7391 - F1: 0.7204
sub_17:Test (Best Model) - Loss: 1.0769 - Accuracy: 0.7101 - F1: 0.6986
sub_27:Test (Best Model) - Loss: 1.0769 - Accuracy: 0.7101 - F1: 0.6986
sub_26:Test (Best Model) - Loss: 0.9380 - Accuracy: 0.7206 - F1: 0.7327
sub_1:Test (Best Model) - Loss: 0.8175 - Accuracy: 0.7391 - F1: 0.7288
sub_13:Test (Best Model) - Loss: 2.0847 - Accuracy: 0.5797 - F1: 0.5646
sub_22:Test (Best Model) - Loss: 2.1116 - Accuracy: 0.5072 - F1: 0.4743
sub_18:Test (Best Model) - Loss: 2.3473 - Accuracy: 0.5588 - F1: 0.5391
sub_28:Test (Best Model) - Loss: 4.4580 - Accuracy: 0.4412 - F1: 0.3558
sub_25:Test (Best Model) - Loss: 0.7902 - Accuracy: 0.8088 - F1: 0.8159
sub_20:Test (Best Model) - Loss: 1.2012 - Accuracy: 0.7059 - F1: 0.6446
sub_9:Test (Best Model) - Loss: 1.4771 - Accuracy: 0.6765 - F1: 0.6116
sub_8:Test (Best Model) - Loss: 2.3583 - Accuracy: 0.6765 - F1: 0.6471
sub_16:Test (Best Model) - Loss: 1.2213 - Accuracy: 0.7353 - F1: 0.7184
sub_15:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.7794 - F1: 0.7745
sub_4:Test (Best Model) - Loss: 2.0997 - Accuracy: 0.7246 - F1: 0.6515
sub_7:Test (Best Model) - Loss: 1.4346 - Accuracy: 0.7059 - F1: 0.6349
sub_12:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.8261 - F1: 0.8302
sub_10:Test (Best Model) - Loss: 1.7789 - Accuracy: 0.6087 - F1: 0.5513
sub_29:Test (Best Model) - Loss: 0.4463 - Accuracy: 0.7647 - F1: 0.7444
sub_2:Test (Best Model) - Loss: 0.9835 - Accuracy: 0.7500 - F1: 0.7537
sub_6:Test (Best Model) - Loss: 1.2525 - Accuracy: 0.7101 - F1: 0.6647
sub_5:Test (Best Model) - Loss: 1.5813 - Accuracy: 0.7059 - F1: 0.6250
sub_13:Test (Best Model) - Loss: 1.0351 - Accuracy: 0.4058 - F1: 0.3754
sub_26:Test (Best Model) - Loss: 1.1610 - Accuracy: 0.6912 - F1: 0.6999
sub_3:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.7681 - F1: 0.7735
sub_11:Test (Best Model) - Loss: 1.5008 - Accuracy: 0.6522 - F1: 0.5916
sub_14:Test (Best Model) - Loss: 2.2997 - Accuracy: 0.5294 - F1: 0.5733
sub_24:Test (Best Model) - Loss: 2.0306 - Accuracy: 0.6765 - F1: 0.6233
sub_23:Test (Best Model) - Loss: 1.6598 - Accuracy: 0.6029 - F1: 0.5170
sub_8:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.6618 - F1: 0.6358
sub_19:Test (Best Model) - Loss: 3.9807 - Accuracy: 0.4265 - F1: 0.3400
sub_27:Test (Best Model) - Loss: 2.4836 - Accuracy: 0.5942 - F1: 0.5434
sub_25:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.7353 - F1: 0.7368
sub_1:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.6667 - F1: 0.6531
sub_17:Test (Best Model) - Loss: 2.4836 - Accuracy: 0.5942 - F1: 0.5434
sub_22:Test (Best Model) - Loss: 1.5264 - Accuracy: 0.6471 - F1: 0.6382
sub_16:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.7353 - F1: 0.7304
sub_9:Test (Best Model) - Loss: 1.5691 - Accuracy: 0.6176 - F1: 0.6007
sub_18:Test (Best Model) - Loss: 1.1590 - Accuracy: 0.6176 - F1: 0.6153
sub_28:Test (Best Model) - Loss: 3.7990 - Accuracy: 0.4559 - F1: 0.3657
sub_21:Test (Best Model) - Loss: 1.0127 - Accuracy: 0.7794 - F1: 0.7549
sub_20:Test (Best Model) - Loss: 2.2684 - Accuracy: 0.6812 - F1: 0.6755
sub_26:Test (Best Model) - Loss: 1.0352 - Accuracy: 0.6029 - F1: 0.6162
sub_29:Test (Best Model) - Loss: 1.8386 - Accuracy: 0.6812 - F1: 0.6104
sub_10:Test (Best Model) - Loss: 1.5849 - Accuracy: 0.6522 - F1: 0.5715
sub_6:Test (Best Model) - Loss: 1.7402 - Accuracy: 0.5942 - F1: 0.5134
sub_7:Test (Best Model) - Loss: 0.8409 - Accuracy: 0.7500 - F1: 0.7607
sub_3:Test (Best Model) - Loss: 0.9566 - Accuracy: 0.7971 - F1: 0.7882
sub_2:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.8696 - F1: 0.8732
sub_5:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.7353 - F1: 0.6631
sub_4:Test (Best Model) - Loss: 1.7116 - Accuracy: 0.6957 - F1: 0.6283
sub_14:Test (Best Model) - Loss: 0.7469 - Accuracy: 0.7500 - F1: 0.7215
sub_8:Test (Best Model) - Loss: 1.9668 - Accuracy: 0.6912 - F1: 0.6555
sub_25:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.7353 - F1: 0.7323
sub_23:Test (Best Model) - Loss: 2.0884 - Accuracy: 0.6324 - F1: 0.5467
sub_24:Test (Best Model) - Loss: 0.7881 - Accuracy: 0.7500 - F1: 0.7715
sub_11:Test (Best Model) - Loss: 1.2400 - Accuracy: 0.7101 - F1: 0.6719
sub_12:Test (Best Model) - Loss: 0.9255 - Accuracy: 0.8088 - F1: 0.8023
sub_15:Test (Best Model) - Loss: 1.0265 - Accuracy: 0.7794 - F1: 0.7794
sub_13:Test (Best Model) - Loss: 2.9240 - Accuracy: 0.4412 - F1: 0.3111
sub_22:Test (Best Model) - Loss: 1.2169 - Accuracy: 0.5735 - F1: 0.5321
sub_10:Test (Best Model) - Loss: 0.8313 - Accuracy: 0.6812 - F1: 0.6323
sub_16:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.7500 - F1: 0.7440
sub_1:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.7971 - F1: 0.8049
sub_18:Test (Best Model) - Loss: 2.9330 - Accuracy: 0.5147 - F1: 0.4828
sub_9:Test (Best Model) - Loss: 1.4646 - Accuracy: 0.6618 - F1: 0.6010
sub_27:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.6912 - F1: 0.6898
sub_21:Test (Best Model) - Loss: 0.2137 - Accuracy: 0.9118 - F1: 0.9143
sub_19:Test (Best Model) - Loss: 2.6353 - Accuracy: 0.5294 - F1: 0.4764
sub_17:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.6912 - F1: 0.6898
sub_5:Test (Best Model) - Loss: 1.4667 - Accuracy: 0.7353 - F1: 0.6532
sub_3:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.6812 - F1: 0.6807
sub_28:Test (Best Model) - Loss: 3.8212 - Accuracy: 0.4706 - F1: 0.3207
sub_20:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.7681 - F1: 0.7697
sub_14:Test (Best Model) - Loss: 0.7177 - Accuracy: 0.7059 - F1: 0.7014
sub_26:Test (Best Model) - Loss: 0.9559 - Accuracy: 0.7941 - F1: 0.8013
sub_29:Test (Best Model) - Loss: 1.7748 - Accuracy: 0.6812 - F1: 0.6343
sub_8:Test (Best Model) - Loss: 1.7618 - Accuracy: 0.6324 - F1: 0.6115
sub_25:Test (Best Model) - Loss: 1.5083 - Accuracy: 0.6765 - F1: 0.6602
sub_2:Test (Best Model) - Loss: 1.6288 - Accuracy: 0.7101 - F1: 0.6698
sub_7:Test (Best Model) - Loss: 0.8230 - Accuracy: 0.7647 - F1: 0.7498
sub_11:Test (Best Model) - Loss: 0.3823 - Accuracy: 0.8551 - F1: 0.8593
sub_6:Test (Best Model) - Loss: 2.6166 - Accuracy: 0.6667 - F1: 0.5993
sub_4:Test (Best Model) - Loss: 0.5385 - Accuracy: 0.7681 - F1: 0.7231
sub_10:Test (Best Model) - Loss: 2.1194 - Accuracy: 0.6957 - F1: 0.6133
sub_12:Test (Best Model) - Loss: 0.7772 - Accuracy: 0.7353 - F1: 0.7279
sub_16:Test (Best Model) - Loss: 0.5158 - Accuracy: 0.8382 - F1: 0.8336
sub_23:Test (Best Model) - Loss: 3.3294 - Accuracy: 0.5362 - F1: 0.4857
sub_24:Test (Best Model) - Loss: 0.9846 - Accuracy: 0.7647 - F1: 0.7782
sub_22:Test (Best Model) - Loss: 1.6503 - Accuracy: 0.6029 - F1: 0.5841
sub_13:Test (Best Model) - Loss: 3.5272 - Accuracy: 0.3971 - F1: 0.2789
sub_21:Test (Best Model) - Loss: 0.9455 - Accuracy: 0.7647 - F1: 0.7231
sub_27:Test (Best Model) - Loss: 1.1064 - Accuracy: 0.6618 - F1: 0.6347
sub_9:Test (Best Model) - Loss: 1.7438 - Accuracy: 0.5588 - F1: 0.5181
sub_19:Test (Best Model) - Loss: 1.9779 - Accuracy: 0.4559 - F1: 0.3905
sub_18:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.5294 - F1: 0.4997
sub_3:Test (Best Model) - Loss: 1.0414 - Accuracy: 0.7246 - F1: 0.7005
sub_5:Test (Best Model) - Loss: 2.0933 - Accuracy: 0.7353 - F1: 0.6550
sub_17:Test (Best Model) - Loss: 1.1064 - Accuracy: 0.6618 - F1: 0.6347
sub_14:Test (Best Model) - Loss: 0.3658 - Accuracy: 0.7941 - F1: 0.7807
sub_16:Test (Best Model) - Loss: 0.5988 - Accuracy: 0.7647 - F1: 0.7673
sub_28:Test (Best Model) - Loss: 4.0624 - Accuracy: 0.5294 - F1: 0.4231
sub_26:Test (Best Model) - Loss: 0.8648 - Accuracy: 0.7206 - F1: 0.7244
sub_25:Test (Best Model) - Loss: 1.4561 - Accuracy: 0.7206 - F1: 0.7052
sub_20:Test (Best Model) - Loss: 0.9339 - Accuracy: 0.6812 - F1: 0.6557
sub_4:Test (Best Model) - Loss: 1.0657 - Accuracy: 0.7536 - F1: 0.6961
sub_2:Test (Best Model) - Loss: 1.9529 - Accuracy: 0.7101 - F1: 0.6460
sub_15:Test (Best Model) - Loss: 3.3328 - Accuracy: 0.6029 - F1: 0.5194
sub_11:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.7536 - F1: 0.7576
sub_23:Test (Best Model) - Loss: 2.4844 - Accuracy: 0.6377 - F1: 0.5759
sub_12:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.6912 - F1: 0.6600
sub_8:Test (Best Model) - Loss: 2.6732 - Accuracy: 0.5147 - F1: 0.5517
sub_1:Test (Best Model) - Loss: 3.1256 - Accuracy: 0.7206 - F1: 0.6509
sub_29:Test (Best Model) - Loss: 2.0706 - Accuracy: 0.6377 - F1: 0.6158
sub_7:Test (Best Model) - Loss: 0.5631 - Accuracy: 0.7353 - F1: 0.7268
sub_22:Test (Best Model) - Loss: 1.1671 - Accuracy: 0.7500 - F1: 0.7304
sub_13:Test (Best Model) - Loss: 2.0061 - Accuracy: 0.3235 - F1: 0.2951
sub_18:Test (Best Model) - Loss: 1.5667 - Accuracy: 0.5588 - F1: 0.5319
sub_24:Test (Best Model) - Loss: 1.0936 - Accuracy: 0.7500 - F1: 0.7127
sub_9:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.6176 - F1: 0.6220
sub_27:Test (Best Model) - Loss: 1.0314 - Accuracy: 0.7794 - F1: 0.7669
sub_20:Test (Best Model) - Loss: 0.9342 - Accuracy: 0.6377 - F1: 0.6229
sub_14:Test (Best Model) - Loss: 0.5386 - Accuracy: 0.8088 - F1: 0.7924
sub_28:Test (Best Model) - Loss: 3.3941 - Accuracy: 0.3676 - F1: 0.2947
sub_17:Test (Best Model) - Loss: 1.0314 - Accuracy: 0.7794 - F1: 0.7669
sub_19:Test (Best Model) - Loss: 2.7709 - Accuracy: 0.5000 - F1: 0.4623
sub_2:Test (Best Model) - Loss: 2.0328 - Accuracy: 0.6522 - F1: 0.5852
sub_21:Test (Best Model) - Loss: 0.2284 - Accuracy: 0.9265 - F1: 0.9292
sub_23:Test (Best Model) - Loss: 2.2954 - Accuracy: 0.5507 - F1: 0.4897
sub_11:Test (Best Model) - Loss: 1.1389 - Accuracy: 0.5652 - F1: 0.5084
sub_15:Test (Best Model) - Loss: 4.5649 - Accuracy: 0.4853 - F1: 0.3522
sub_22:Test (Best Model) - Loss: 1.8502 - Accuracy: 0.5882 - F1: 0.5811
sub_4:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.7391 - F1: 0.6877
sub_1:Test (Best Model) - Loss: 2.2215 - Accuracy: 0.6618 - F1: 0.6177
sub_24:Test (Best Model) - Loss: 1.0765 - Accuracy: 0.6471 - F1: 0.6361
sub_12:Test (Best Model) - Loss: 0.4406 - Accuracy: 0.8529 - F1: 0.8571
sub_29:Test (Best Model) - Loss: 1.3436 - Accuracy: 0.6812 - F1: 0.6268
sub_27:Test (Best Model) - Loss: 0.5084 - Accuracy: 0.8235 - F1: 0.8260
sub_13:Test (Best Model) - Loss: 3.0480 - Accuracy: 0.4706 - F1: 0.3294
sub_17:Test (Best Model) - Loss: 0.5084 - Accuracy: 0.8235 - F1: 0.8260
sub_14:Test (Best Model) - Loss: 1.6294 - Accuracy: 0.6912 - F1: 0.6439
sub_20:Test (Best Model) - Loss: 1.4188 - Accuracy: 0.7391 - F1: 0.7223
sub_23:Test (Best Model) - Loss: 2.4790 - Accuracy: 0.5797 - F1: 0.5286
sub_28:Test (Best Model) - Loss: 2.6576 - Accuracy: 0.4706 - F1: 0.3886
sub_2:Test (Best Model) - Loss: 0.6159 - Accuracy: 0.7246 - F1: 0.7224
sub_24:Test (Best Model) - Loss: 0.3542 - Accuracy: 0.8529 - F1: 0.8628
sub_12:Test (Best Model) - Loss: 0.5044 - Accuracy: 0.7794 - F1: 0.7765
sub_15:Test (Best Model) - Loss: 3.0026 - Accuracy: 0.5000 - F1: 0.3896
sub_27:Test (Best Model) - Loss: 2.2910 - Accuracy: 0.6471 - F1: 0.5931
sub_1:Test (Best Model) - Loss: 1.8815 - Accuracy: 0.7206 - F1: 0.6680
sub_29:Test (Best Model) - Loss: 1.6755 - Accuracy: 0.6812 - F1: 0.6240
sub_28:Test (Best Model) - Loss: 4.1799 - Accuracy: 0.2941 - F1: 0.2279
sub_21:Test (Best Model) - Loss: 0.7744 - Accuracy: 0.8088 - F1: 0.7894
sub_17:Test (Best Model) - Loss: 2.2910 - Accuracy: 0.6471 - F1: 0.5931
sub_23:Test (Best Model) - Loss: 2.7615 - Accuracy: 0.5652 - F1: 0.5006
sub_13:Test (Best Model) - Loss: 4.0379 - Accuracy: 0.4853 - F1: 0.4031
sub_15:Test (Best Model) - Loss: 2.4419 - Accuracy: 0.5441 - F1: 0.4473
sub_1:Test (Best Model) - Loss: 1.9911 - Accuracy: 0.7059 - F1: 0.6353
sub_21:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.8382 - F1: 0.8314
sub_15:Test (Best Model) - Loss: 2.8220 - Accuracy: 0.5735 - F1: 0.4874
sub_1:Test (Best Model) - Loss: 2.0624 - Accuracy: 0.7206 - F1: 0.6509

=== Summary Results ===

acc: 67.66 ± 9.03
F1: 64.46 ± 10.19
acc-in: 96.86 ± 2.24
F1-in: 96.75 ± 2.31
