lr: 1e-05
sub_8:Test (Best Model) - Loss: 1.4244 - Accuracy: 0.4706 - F1: 0.4462
sub_10:Test (Best Model) - Loss: 0.9082 - Accuracy: 0.4706 - F1: 0.4831
sub_11:Test (Best Model) - Loss: 0.9612 - Accuracy: 0.6377 - F1: 0.6083
sub_18:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.5507 - F1: 0.5562
sub_14:Test (Best Model) - Loss: 1.0468 - Accuracy: 0.5882 - F1: 0.5433
sub_20:Test (Best Model) - Loss: 0.8117 - Accuracy: 0.7353 - F1: 0.7132
sub_15:Test (Best Model) - Loss: 0.9448 - Accuracy: 0.4853 - F1: 0.4107
sub_3:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.9118 - F1: 0.9166
sub_16:Test (Best Model) - Loss: 0.9177 - Accuracy: 0.6324 - F1: 0.6281
sub_4:Test (Best Model) - Loss: 0.7881 - Accuracy: 0.5652 - F1: 0.5174
sub_26:Test (Best Model) - Loss: 0.8181 - Accuracy: 0.5942 - F1: 0.5720
sub_13:Test (Best Model) - Loss: 1.2009 - Accuracy: 0.4265 - F1: 0.3768
sub_2:Test (Best Model) - Loss: 0.9112 - Accuracy: 0.5072 - F1: 0.4437
sub_24:Test (Best Model) - Loss: 1.0706 - Accuracy: 0.5147 - F1: 0.4529
sub_28:Test (Best Model) - Loss: 1.1459 - Accuracy: 0.3676 - F1: 0.3161
sub_25:Test (Best Model) - Loss: 0.3683 - Accuracy: 0.8841 - F1: 0.8877
sub_12:Test (Best Model) - Loss: 0.9264 - Accuracy: 0.6029 - F1: 0.5641
sub_22:Test (Best Model) - Loss: 1.1137 - Accuracy: 0.3824 - F1: 0.3811
sub_21:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.8676 - F1: 0.8610
sub_7:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.7794 - F1: 0.7793
sub_6:Test (Best Model) - Loss: 1.1528 - Accuracy: 0.6029 - F1: 0.5359
sub_23:Test (Best Model) - Loss: 0.8659 - Accuracy: 0.5797 - F1: 0.5439
sub_17:Test (Best Model) - Loss: 0.6124 - Accuracy: 0.7536 - F1: 0.7421
sub_29:Test (Best Model) - Loss: 0.7875 - Accuracy: 0.4706 - F1: 0.5123
sub_27:Test (Best Model) - Loss: 0.6124 - Accuracy: 0.7536 - F1: 0.7421
sub_19:Test (Best Model) - Loss: 1.4895 - Accuracy: 0.3676 - F1: 0.3316
sub_5:Test (Best Model) - Loss: 1.1540 - Accuracy: 0.5882 - F1: 0.5445
sub_9:Test (Best Model) - Loss: 0.7445 - Accuracy: 0.6765 - F1: 0.6791
sub_3:Test (Best Model) - Loss: 0.9383 - Accuracy: 0.5882 - F1: 0.5815
sub_16:Test (Best Model) - Loss: 0.9667 - Accuracy: 0.5588 - F1: 0.5555
sub_10:Test (Best Model) - Loss: 1.2754 - Accuracy: 0.4265 - F1: 0.4494
sub_8:Test (Best Model) - Loss: 1.0377 - Accuracy: 0.6029 - F1: 0.5348
sub_1:Test (Best Model) - Loss: 0.8182 - Accuracy: 0.6618 - F1: 0.6629
sub_4:Test (Best Model) - Loss: 0.8761 - Accuracy: 0.6522 - F1: 0.6008
sub_21:Test (Best Model) - Loss: 0.9197 - Accuracy: 0.6618 - F1: 0.6697
sub_20:Test (Best Model) - Loss: 1.0211 - Accuracy: 0.5735 - F1: 0.5267
sub_14:Test (Best Model) - Loss: 1.2954 - Accuracy: 0.4706 - F1: 0.3946
sub_12:Test (Best Model) - Loss: 0.9040 - Accuracy: 0.6765 - F1: 0.6991
sub_26:Test (Best Model) - Loss: 0.8684 - Accuracy: 0.5652 - F1: 0.5819
sub_18:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.5652 - F1: 0.5475
sub_28:Test (Best Model) - Loss: 1.1344 - Accuracy: 0.4412 - F1: 0.3871
sub_15:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.7500 - F1: 0.7624
sub_24:Test (Best Model) - Loss: 0.9207 - Accuracy: 0.5294 - F1: 0.4699
sub_11:Test (Best Model) - Loss: 0.7387 - Accuracy: 0.7536 - F1: 0.7262
sub_2:Test (Best Model) - Loss: 0.7839 - Accuracy: 0.7101 - F1: 0.6829
sub_17:Test (Best Model) - Loss: 0.7361 - Accuracy: 0.7536 - F1: 0.7525
sub_25:Test (Best Model) - Loss: 0.4176 - Accuracy: 0.9275 - F1: 0.9273
sub_27:Test (Best Model) - Loss: 0.7361 - Accuracy: 0.7536 - F1: 0.7525
sub_22:Test (Best Model) - Loss: 1.1741 - Accuracy: 0.3529 - F1: 0.3713
sub_7:Test (Best Model) - Loss: 0.7723 - Accuracy: 0.8235 - F1: 0.8186
sub_13:Test (Best Model) - Loss: 1.0569 - Accuracy: 0.5735 - F1: 0.5272
sub_6:Test (Best Model) - Loss: 0.9415 - Accuracy: 0.6029 - F1: 0.5987
sub_8:Test (Best Model) - Loss: 1.1288 - Accuracy: 0.4118 - F1: 0.3584
sub_19:Test (Best Model) - Loss: 1.6209 - Accuracy: 0.3088 - F1: 0.3009
sub_23:Test (Best Model) - Loss: 0.9462 - Accuracy: 0.5507 - F1: 0.4930
sub_4:Test (Best Model) - Loss: 0.7412 - Accuracy: 0.6667 - F1: 0.6268
sub_5:Test (Best Model) - Loss: 1.0744 - Accuracy: 0.5441 - F1: 0.4930
sub_9:Test (Best Model) - Loss: 0.7763 - Accuracy: 0.6765 - F1: 0.6863
sub_29:Test (Best Model) - Loss: 0.7563 - Accuracy: 0.5735 - F1: 0.5841
sub_16:Test (Best Model) - Loss: 0.9487 - Accuracy: 0.5735 - F1: 0.5977
sub_3:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.8529 - F1: 0.8628
sub_10:Test (Best Model) - Loss: 1.2351 - Accuracy: 0.4265 - F1: 0.4233
sub_26:Test (Best Model) - Loss: 0.8894 - Accuracy: 0.5507 - F1: 0.5263
sub_21:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.8088 - F1: 0.8133
sub_20:Test (Best Model) - Loss: 0.8217 - Accuracy: 0.6912 - F1: 0.6673
sub_15:Test (Best Model) - Loss: 0.7916 - Accuracy: 0.6765 - F1: 0.6983
sub_12:Test (Best Model) - Loss: 0.5886 - Accuracy: 0.7500 - F1: 0.7405
sub_14:Test (Best Model) - Loss: 1.6801 - Accuracy: 0.4412 - F1: 0.3524
sub_11:Test (Best Model) - Loss: 0.9702 - Accuracy: 0.6232 - F1: 0.5590
sub_25:Test (Best Model) - Loss: 0.3819 - Accuracy: 0.8696 - F1: 0.8679
sub_18:Test (Best Model) - Loss: 0.5061 - Accuracy: 0.7826 - F1: 0.7619
sub_24:Test (Best Model) - Loss: 0.8907 - Accuracy: 0.6029 - F1: 0.5625
sub_28:Test (Best Model) - Loss: 1.1792 - Accuracy: 0.4412 - F1: 0.3519
sub_19:Test (Best Model) - Loss: 1.2191 - Accuracy: 0.4853 - F1: 0.4853
sub_17:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.6522 - F1: 0.6339
sub_27:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.6522 - F1: 0.6339
sub_7:Test (Best Model) - Loss: 0.6237 - Accuracy: 0.5882 - F1: 0.5417
sub_2:Test (Best Model) - Loss: 0.8491 - Accuracy: 0.5942 - F1: 0.5063
sub_29:Test (Best Model) - Loss: 0.9192 - Accuracy: 0.5441 - F1: 0.5322
sub_5:Test (Best Model) - Loss: 1.0925 - Accuracy: 0.7206 - F1: 0.6518
sub_4:Test (Best Model) - Loss: 0.7764 - Accuracy: 0.6232 - F1: 0.5887
sub_1:Test (Best Model) - Loss: 0.7372 - Accuracy: 0.6765 - F1: 0.6792
sub_6:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.4412 - F1: 0.3532
sub_8:Test (Best Model) - Loss: 1.0832 - Accuracy: 0.6471 - F1: 0.5937
sub_22:Test (Best Model) - Loss: 1.1781 - Accuracy: 0.5147 - F1: 0.4349
sub_16:Test (Best Model) - Loss: 0.7795 - Accuracy: 0.6765 - F1: 0.6740
sub_13:Test (Best Model) - Loss: 1.1779 - Accuracy: 0.4706 - F1: 0.4030
sub_23:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.7536 - F1: 0.7508
sub_26:Test (Best Model) - Loss: 0.9326 - Accuracy: 0.5942 - F1: 0.6163
sub_3:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.7206 - F1: 0.6827
sub_10:Test (Best Model) - Loss: 0.7663 - Accuracy: 0.6618 - F1: 0.6875
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.4118 - F1: 0.3606
sub_2:Test (Best Model) - Loss: 1.1109 - Accuracy: 0.6087 - F1: 0.5554
sub_15:Test (Best Model) - Loss: 0.5262 - Accuracy: 0.9118 - F1: 0.9145
sub_14:Test (Best Model) - Loss: 2.0289 - Accuracy: 0.3971 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7670 - Accuracy: 0.6667 - F1: 0.6511
sub_17:Test (Best Model) - Loss: 0.5153 - Accuracy: 0.9130 - F1: 0.9160
sub_20:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.6471 - F1: 0.6464
sub_18:Test (Best Model) - Loss: 0.7740 - Accuracy: 0.6957 - F1: 0.7046
sub_28:Test (Best Model) - Loss: 0.9661 - Accuracy: 0.5441 - F1: 0.5314
sub_27:Test (Best Model) - Loss: 0.5153 - Accuracy: 0.9130 - F1: 0.9160
sub_9:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.8529 - F1: 0.8620
sub_24:Test (Best Model) - Loss: 0.8968 - Accuracy: 0.6176 - F1: 0.5909
sub_5:Test (Best Model) - Loss: 1.2096 - Accuracy: 0.5294 - F1: 0.4985
sub_7:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.6912 - F1: 0.6814
sub_21:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.7647 - F1: 0.7564
sub_12:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.6471 - F1: 0.6359
sub_1:Test (Best Model) - Loss: 0.7388 - Accuracy: 0.6912 - F1: 0.6859
sub_29:Test (Best Model) - Loss: 0.8266 - Accuracy: 0.6029 - F1: 0.6235
sub_8:Test (Best Model) - Loss: 1.1579 - Accuracy: 0.6324 - F1: 0.5807
sub_25:Test (Best Model) - Loss: 0.5493 - Accuracy: 0.7681 - F1: 0.7534
sub_23:Test (Best Model) - Loss: 0.8898 - Accuracy: 0.6232 - F1: 0.6306
sub_26:Test (Best Model) - Loss: 0.9259 - Accuracy: 0.5652 - F1: 0.5342
sub_4:Test (Best Model) - Loss: 0.5713 - Accuracy: 0.7246 - F1: 0.6700
sub_16:Test (Best Model) - Loss: 0.9379 - Accuracy: 0.6618 - F1: 0.6745
sub_22:Test (Best Model) - Loss: 1.2040 - Accuracy: 0.3824 - F1: 0.3864
sub_10:Test (Best Model) - Loss: 1.0150 - Accuracy: 0.5294 - F1: 0.5424
sub_2:Test (Best Model) - Loss: 0.9061 - Accuracy: 0.6957 - F1: 0.6784
sub_8:Test (Best Model) - Loss: 1.0305 - Accuracy: 0.5294 - F1: 0.4749
sub_6:Test (Best Model) - Loss: 1.0723 - Accuracy: 0.4706 - F1: 0.4345
sub_3:Test (Best Model) - Loss: 0.9970 - Accuracy: 0.6029 - F1: 0.5485
sub_15:Test (Best Model) - Loss: 0.8303 - Accuracy: 0.6324 - F1: 0.6581
sub_13:Test (Best Model) - Loss: 1.1455 - Accuracy: 0.4706 - F1: 0.4144
sub_17:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.8406 - F1: 0.8465
sub_20:Test (Best Model) - Loss: 1.0748 - Accuracy: 0.5882 - F1: 0.5321
sub_5:Test (Best Model) - Loss: 1.1668 - Accuracy: 0.6324 - F1: 0.5728
sub_14:Test (Best Model) - Loss: 1.6245 - Accuracy: 0.4265 - F1: 0.3400
sub_19:Test (Best Model) - Loss: 2.1651 - Accuracy: 0.2647 - F1: 0.2635
sub_9:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6912 - F1: 0.6487
sub_27:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.8406 - F1: 0.8465
sub_26:Test (Best Model) - Loss: 1.0214 - Accuracy: 0.5294 - F1: 0.5012
sub_28:Test (Best Model) - Loss: 1.2114 - Accuracy: 0.4706 - F1: 0.4022
sub_11:Test (Best Model) - Loss: 0.7459 - Accuracy: 0.7536 - F1: 0.7464
sub_1:Test (Best Model) - Loss: 0.8223 - Accuracy: 0.5882 - F1: 0.5606
sub_12:Test (Best Model) - Loss: 0.8634 - Accuracy: 0.6176 - F1: 0.5953
sub_18:Test (Best Model) - Loss: 0.7732 - Accuracy: 0.6667 - F1: 0.6512
sub_24:Test (Best Model) - Loss: 0.9088 - Accuracy: 0.6029 - F1: 0.5973
sub_21:Test (Best Model) - Loss: 0.7616 - Accuracy: 0.7059 - F1: 0.6926
sub_4:Test (Best Model) - Loss: 0.8565 - Accuracy: 0.7391 - F1: 0.6854
sub_25:Test (Best Model) - Loss: 0.3992 - Accuracy: 0.9130 - F1: 0.9134
sub_7:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.9331 - Accuracy: 0.5882 - F1: 0.5492
sub_10:Test (Best Model) - Loss: 1.0123 - Accuracy: 0.4853 - F1: 0.3936
sub_23:Test (Best Model) - Loss: 0.8073 - Accuracy: 0.6667 - F1: 0.6760
sub_19:Test (Best Model) - Loss: 1.1680 - Accuracy: 0.5294 - F1: 0.4738
sub_15:Test (Best Model) - Loss: 0.9908 - Accuracy: 0.6176 - F1: 0.5537
sub_22:Test (Best Model) - Loss: 1.1185 - Accuracy: 0.4412 - F1: 0.4104
sub_3:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.5797 - F1: 0.5352
sub_17:Test (Best Model) - Loss: 0.9107 - Accuracy: 0.6232 - F1: 0.6105
sub_1:Test (Best Model) - Loss: 1.1280 - Accuracy: 0.5735 - F1: 0.5384
sub_29:Test (Best Model) - Loss: 0.7941 - Accuracy: 0.5441 - F1: 0.5655
sub_13:Test (Best Model) - Loss: 1.2609 - Accuracy: 0.4118 - F1: 0.3439
sub_27:Test (Best Model) - Loss: 0.9107 - Accuracy: 0.6232 - F1: 0.6105
sub_6:Test (Best Model) - Loss: 1.1654 - Accuracy: 0.4559 - F1: 0.4224
sub_14:Test (Best Model) - Loss: 0.7186 - Accuracy: 0.7353 - F1: 0.7482
sub_24:Test (Best Model) - Loss: 0.9293 - Accuracy: 0.6324 - F1: 0.6248
sub_20:Test (Best Model) - Loss: 0.9624 - Accuracy: 0.6471 - F1: 0.5888
sub_26:Test (Best Model) - Loss: 0.9937 - Accuracy: 0.6324 - F1: 0.6187
sub_9:Test (Best Model) - Loss: 0.8941 - Accuracy: 0.6618 - F1: 0.6773
sub_7:Test (Best Model) - Loss: 0.9752 - Accuracy: 0.6765 - F1: 0.6112
sub_8:Test (Best Model) - Loss: 0.7669 - Accuracy: 0.7353 - F1: 0.6599
sub_21:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.7059 - F1: 0.6683
sub_11:Test (Best Model) - Loss: 0.7754 - Accuracy: 0.6957 - F1: 0.6526
sub_2:Test (Best Model) - Loss: 0.6188 - Accuracy: 0.7647 - F1: 0.7520
sub_5:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.6765 - F1: 0.6352
sub_28:Test (Best Model) - Loss: 1.7118 - Accuracy: 0.3824 - F1: 0.3068
sub_12:Test (Best Model) - Loss: 1.0588 - Accuracy: 0.5217 - F1: 0.4915
sub_25:Test (Best Model) - Loss: 0.9418 - Accuracy: 0.6324 - F1: 0.5655
sub_4:Test (Best Model) - Loss: 0.7697 - Accuracy: 0.7536 - F1: 0.7513
sub_10:Test (Best Model) - Loss: 1.1099 - Accuracy: 0.5147 - F1: 0.5185
sub_23:Test (Best Model) - Loss: 1.4377 - Accuracy: 0.3235 - F1: 0.2548
sub_3:Test (Best Model) - Loss: 1.0574 - Accuracy: 0.6667 - F1: 0.6082
sub_19:Test (Best Model) - Loss: 0.9219 - Accuracy: 0.5294 - F1: 0.4471
sub_22:Test (Best Model) - Loss: 0.9298 - Accuracy: 0.6087 - F1: 0.5937
sub_15:Test (Best Model) - Loss: 0.9378 - Accuracy: 0.6176 - F1: 0.5395
sub_16:Test (Best Model) - Loss: 0.7871 - Accuracy: 0.8235 - F1: 0.8256
sub_6:Test (Best Model) - Loss: 1.0315 - Accuracy: 0.4493 - F1: 0.4199
sub_18:Test (Best Model) - Loss: 1.0306 - Accuracy: 0.6471 - F1: 0.5936
sub_7:Test (Best Model) - Loss: 0.9618 - Accuracy: 0.6471 - F1: 0.6471
sub_2:Test (Best Model) - Loss: 0.8128 - Accuracy: 0.7353 - F1: 0.7433
sub_14:Test (Best Model) - Loss: 0.9343 - Accuracy: 0.3971 - F1: 0.3687
sub_17:Test (Best Model) - Loss: 1.1102 - Accuracy: 0.5362 - F1: 0.5200
sub_27:Test (Best Model) - Loss: 1.1102 - Accuracy: 0.5362 - F1: 0.5200
sub_28:Test (Best Model) - Loss: 1.5355 - Accuracy: 0.3824 - F1: 0.3002
sub_8:Test (Best Model) - Loss: 0.8848 - Accuracy: 0.6912 - F1: 0.6650
sub_24:Test (Best Model) - Loss: 0.9174 - Accuracy: 0.6618 - F1: 0.5900
sub_13:Test (Best Model) - Loss: 0.9301 - Accuracy: 0.5362 - F1: 0.5031
sub_26:Test (Best Model) - Loss: 1.0715 - Accuracy: 0.5294 - F1: 0.4541
sub_12:Test (Best Model) - Loss: 1.0037 - Accuracy: 0.5797 - F1: 0.5510
sub_20:Test (Best Model) - Loss: 0.7934 - Accuracy: 0.7206 - F1: 0.6528
sub_29:Test (Best Model) - Loss: 0.5695 - Accuracy: 0.7941 - F1: 0.7785
sub_5:Test (Best Model) - Loss: 0.9297 - Accuracy: 0.7059 - F1: 0.6979
sub_9:Test (Best Model) - Loss: 0.9116 - Accuracy: 0.5588 - F1: 0.5123
sub_1:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.8116 - F1: 0.8184
sub_23:Test (Best Model) - Loss: 1.0245 - Accuracy: 0.4559 - F1: 0.4239
sub_22:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.3623 - F1: 0.3687
sub_25:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.7206 - F1: 0.7194
sub_10:Test (Best Model) - Loss: 0.9911 - Accuracy: 0.4265 - F1: 0.3540
sub_21:Test (Best Model) - Loss: 0.5482 - Accuracy: 0.8088 - F1: 0.7753
sub_11:Test (Best Model) - Loss: 0.7514 - Accuracy: 0.6812 - F1: 0.6399
sub_6:Test (Best Model) - Loss: 0.9442 - Accuracy: 0.5797 - F1: 0.5170
sub_4:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.8116 - F1: 0.8096
sub_3:Test (Best Model) - Loss: 0.9952 - Accuracy: 0.4928 - F1: 0.4872
sub_15:Test (Best Model) - Loss: 0.9682 - Accuracy: 0.6618 - F1: 0.6419
sub_7:Test (Best Model) - Loss: 0.9982 - Accuracy: 0.6176 - F1: 0.5450
sub_19:Test (Best Model) - Loss: 0.9661 - Accuracy: 0.5735 - F1: 0.5192
sub_18:Test (Best Model) - Loss: 0.9963 - Accuracy: 0.6324 - F1: 0.6014
sub_16:Test (Best Model) - Loss: 0.8803 - Accuracy: 0.7500 - F1: 0.7486
sub_17:Test (Best Model) - Loss: 1.0814 - Accuracy: 0.4493 - F1: 0.4371
sub_8:Test (Best Model) - Loss: 0.7934 - Accuracy: 0.6912 - F1: 0.6281
sub_27:Test (Best Model) - Loss: 1.0814 - Accuracy: 0.4493 - F1: 0.4371
sub_26:Test (Best Model) - Loss: 0.9354 - Accuracy: 0.5735 - F1: 0.5201
sub_10:Test (Best Model) - Loss: 0.9253 - Accuracy: 0.6029 - F1: 0.6172
sub_13:Test (Best Model) - Loss: 1.0564 - Accuracy: 0.4928 - F1: 0.4720
sub_5:Test (Best Model) - Loss: 1.0128 - Accuracy: 0.5735 - F1: 0.5275
sub_9:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.7206 - F1: 0.6898
sub_29:Test (Best Model) - Loss: 0.8592 - Accuracy: 0.5147 - F1: 0.4985
sub_23:Test (Best Model) - Loss: 1.3167 - Accuracy: 0.4853 - F1: 0.3641
sub_12:Test (Best Model) - Loss: 0.9862 - Accuracy: 0.6087 - F1: 0.6057
sub_2:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.7206 - F1: 0.7230
sub_14:Test (Best Model) - Loss: 1.1283 - Accuracy: 0.3235 - F1: 0.2969
sub_22:Test (Best Model) - Loss: 1.0825 - Accuracy: 0.5072 - F1: 0.4756
sub_25:Test (Best Model) - Loss: 0.8726 - Accuracy: 0.7206 - F1: 0.7092
sub_20:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.6618 - F1: 0.6007
sub_24:Test (Best Model) - Loss: 0.8854 - Accuracy: 0.5588 - F1: 0.5213
sub_28:Test (Best Model) - Loss: 1.5646 - Accuracy: 0.4412 - F1: 0.3558
sub_1:Test (Best Model) - Loss: 0.9938 - Accuracy: 0.5942 - F1: 0.5827
sub_7:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.6765 - F1: 0.6184
sub_4:Test (Best Model) - Loss: 0.5840 - Accuracy: 0.7971 - F1: 0.7783
sub_3:Test (Best Model) - Loss: 1.0436 - Accuracy: 0.5797 - F1: 0.5412
sub_21:Test (Best Model) - Loss: 0.5279 - Accuracy: 0.7059 - F1: 0.6564
sub_19:Test (Best Model) - Loss: 0.8726 - Accuracy: 0.6471 - F1: 0.6161
sub_15:Test (Best Model) - Loss: 0.7633 - Accuracy: 0.7500 - F1: 0.7474
sub_11:Test (Best Model) - Loss: 0.8488 - Accuracy: 0.7391 - F1: 0.6961
sub_18:Test (Best Model) - Loss: 1.1687 - Accuracy: 0.4265 - F1: 0.4333
sub_6:Test (Best Model) - Loss: 0.8489 - Accuracy: 0.5942 - F1: 0.5501
sub_8:Test (Best Model) - Loss: 0.7909 - Accuracy: 0.7794 - F1: 0.7840
sub_16:Test (Best Model) - Loss: 0.9535 - Accuracy: 0.4853 - F1: 0.5023
sub_26:Test (Best Model) - Loss: 1.0847 - Accuracy: 0.5588 - F1: 0.5310
sub_17:Test (Best Model) - Loss: 0.8983 - Accuracy: 0.6522 - F1: 0.6543
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.7059 - F1: 0.6700
sub_13:Test (Best Model) - Loss: 1.1520 - Accuracy: 0.5797 - F1: 0.5025
sub_20:Test (Best Model) - Loss: 0.8444 - Accuracy: 0.6324 - F1: 0.5669
sub_25:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.7206 - F1: 0.7225
sub_7:Test (Best Model) - Loss: 0.9770 - Accuracy: 0.6471 - F1: 0.5803
sub_27:Test (Best Model) - Loss: 0.8983 - Accuracy: 0.6522 - F1: 0.6543
sub_1:Test (Best Model) - Loss: 0.8745 - Accuracy: 0.6232 - F1: 0.6225
sub_28:Test (Best Model) - Loss: 2.0855 - Accuracy: 0.3676 - F1: 0.2806
sub_10:Test (Best Model) - Loss: 1.0446 - Accuracy: 0.5147 - F1: 0.5094
sub_14:Test (Best Model) - Loss: 0.8735 - Accuracy: 0.6618 - F1: 0.6593
sub_9:Test (Best Model) - Loss: 0.7926 - Accuracy: 0.5882 - F1: 0.5443
sub_11:Test (Best Model) - Loss: 0.8073 - Accuracy: 0.7681 - F1: 0.7539
sub_2:Test (Best Model) - Loss: 0.8237 - Accuracy: 0.5735 - F1: 0.5559
sub_24:Test (Best Model) - Loss: 0.9913 - Accuracy: 0.6324 - F1: 0.5556
sub_4:Test (Best Model) - Loss: 1.0167 - Accuracy: 0.4783 - F1: 0.4760
sub_23:Test (Best Model) - Loss: 1.2433 - Accuracy: 0.4118 - F1: 0.3521
sub_12:Test (Best Model) - Loss: 0.8371 - Accuracy: 0.6232 - F1: 0.6372
sub_19:Test (Best Model) - Loss: 0.8717 - Accuracy: 0.6324 - F1: 0.6393
sub_22:Test (Best Model) - Loss: 0.9527 - Accuracy: 0.5652 - F1: 0.5376
sub_21:Test (Best Model) - Loss: 0.5807 - Accuracy: 0.7941 - F1: 0.7607
sub_29:Test (Best Model) - Loss: 0.7325 - Accuracy: 0.7206 - F1: 0.7103
sub_3:Test (Best Model) - Loss: 0.9610 - Accuracy: 0.5797 - F1: 0.5563
sub_18:Test (Best Model) - Loss: 1.0407 - Accuracy: 0.5735 - F1: 0.5195
sub_6:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.7391 - F1: 0.7226
sub_5:Test (Best Model) - Loss: 0.9389 - Accuracy: 0.6618 - F1: 0.6488
sub_1:Test (Best Model) - Loss: 0.9723 - Accuracy: 0.5652 - F1: 0.4951
sub_10:Test (Best Model) - Loss: 0.8771 - Accuracy: 0.6957 - F1: 0.6294
sub_17:Test (Best Model) - Loss: 1.0543 - Accuracy: 0.5942 - F1: 0.5511
sub_26:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.5882 - F1: 0.5519
sub_27:Test (Best Model) - Loss: 1.0543 - Accuracy: 0.5942 - F1: 0.5511
sub_8:Test (Best Model) - Loss: 0.9598 - Accuracy: 0.6765 - F1: 0.6208
sub_15:Test (Best Model) - Loss: 0.7687 - Accuracy: 0.7206 - F1: 0.7145
sub_20:Test (Best Model) - Loss: 0.7712 - Accuracy: 0.7353 - F1: 0.7010
sub_7:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.6912 - F1: 0.6866
sub_2:Test (Best Model) - Loss: 0.8558 - Accuracy: 0.6471 - F1: 0.5923
sub_24:Test (Best Model) - Loss: 0.9150 - Accuracy: 0.6618 - F1: 0.5994
sub_4:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.6522 - F1: 0.6010
sub_16:Test (Best Model) - Loss: 1.0294 - Accuracy: 0.5588 - F1: 0.5270
sub_9:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.7206 - F1: 0.7073
sub_19:Test (Best Model) - Loss: 1.0987 - Accuracy: 0.5294 - F1: 0.4570
sub_29:Test (Best Model) - Loss: 0.6110 - Accuracy: 0.7647 - F1: 0.7456
sub_25:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.7059 - F1: 0.6492
sub_23:Test (Best Model) - Loss: 1.1471 - Accuracy: 0.4265 - F1: 0.3044
sub_3:Test (Best Model) - Loss: 0.7314 - Accuracy: 0.7681 - F1: 0.7653
sub_21:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.6618 - F1: 0.6074
sub_22:Test (Best Model) - Loss: 1.0159 - Accuracy: 0.4203 - F1: 0.4308
sub_6:Test (Best Model) - Loss: 0.9204 - Accuracy: 0.5942 - F1: 0.5676
sub_13:Test (Best Model) - Loss: 0.9366 - Accuracy: 0.4638 - F1: 0.4812
sub_14:Test (Best Model) - Loss: 0.9702 - Accuracy: 0.5147 - F1: 0.5519
sub_11:Test (Best Model) - Loss: 0.5531 - Accuracy: 0.7826 - F1: 0.7590
sub_26:Test (Best Model) - Loss: 0.9528 - Accuracy: 0.5882 - F1: 0.6257
sub_12:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.7826 - F1: 0.7797
sub_5:Test (Best Model) - Loss: 1.0408 - Accuracy: 0.5441 - F1: 0.4837
sub_28:Test (Best Model) - Loss: 1.2757 - Accuracy: 0.3971 - F1: 0.3217
sub_10:Test (Best Model) - Loss: 1.1863 - Accuracy: 0.4928 - F1: 0.4012
sub_1:Test (Best Model) - Loss: 0.8027 - Accuracy: 0.6522 - F1: 0.6588
sub_20:Test (Best Model) - Loss: 1.1236 - Accuracy: 0.5072 - F1: 0.4840
sub_18:Test (Best Model) - Loss: 0.9689 - Accuracy: 0.6471 - F1: 0.5930
sub_8:Test (Best Model) - Loss: 1.1096 - Accuracy: 0.5735 - F1: 0.5916
sub_19:Test (Best Model) - Loss: 1.1348 - Accuracy: 0.5000 - F1: 0.4554
sub_17:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.7941 - F1: 0.7842
sub_24:Test (Best Model) - Loss: 1.0223 - Accuracy: 0.5882 - F1: 0.5644
sub_27:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.7941 - F1: 0.7842
sub_15:Test (Best Model) - Loss: 0.9615 - Accuracy: 0.5441 - F1: 0.4529
sub_23:Test (Best Model) - Loss: 1.0734 - Accuracy: 0.4493 - F1: 0.4106
sub_16:Test (Best Model) - Loss: 0.8638 - Accuracy: 0.6765 - F1: 0.6659
sub_2:Test (Best Model) - Loss: 0.8468 - Accuracy: 0.6087 - F1: 0.5318
sub_4:Test (Best Model) - Loss: 0.7426 - Accuracy: 0.6667 - F1: 0.6537
sub_3:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.7826 - F1: 0.7917
sub_25:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.7059 - F1: 0.7059
sub_7:Test (Best Model) - Loss: 0.9565 - Accuracy: 0.6912 - F1: 0.6295
sub_9:Test (Best Model) - Loss: 0.8737 - Accuracy: 0.6029 - F1: 0.5327
sub_22:Test (Best Model) - Loss: 1.0670 - Accuracy: 0.5294 - F1: 0.4805
sub_11:Test (Best Model) - Loss: 0.9304 - Accuracy: 0.6667 - F1: 0.6434
sub_5:Test (Best Model) - Loss: 1.5903 - Accuracy: 0.4706 - F1: 0.3250
sub_6:Test (Best Model) - Loss: 0.8375 - Accuracy: 0.6522 - F1: 0.6302
sub_28:Test (Best Model) - Loss: 1.5661 - Accuracy: 0.2500 - F1: 0.1826
sub_13:Test (Best Model) - Loss: 0.9371 - Accuracy: 0.6522 - F1: 0.6265
sub_20:Test (Best Model) - Loss: 0.8476 - Accuracy: 0.6812 - F1: 0.6752
sub_26:Test (Best Model) - Loss: 1.1981 - Accuracy: 0.4265 - F1: 0.4040
sub_14:Test (Best Model) - Loss: 0.8326 - Accuracy: 0.6176 - F1: 0.6418
sub_12:Test (Best Model) - Loss: 0.9124 - Accuracy: 0.6029 - F1: 0.6164
sub_10:Test (Best Model) - Loss: 0.7905 - Accuracy: 0.7101 - F1: 0.6775
sub_21:Test (Best Model) - Loss: 0.4276 - Accuracy: 0.8824 - F1: 0.8776
sub_1:Test (Best Model) - Loss: 1.1468 - Accuracy: 0.6324 - F1: 0.5559
sub_29:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.8382 - F1: 0.8429
sub_19:Test (Best Model) - Loss: 1.1895 - Accuracy: 0.3824 - F1: 0.3524
sub_2:Test (Best Model) - Loss: 1.0009 - Accuracy: 0.5652 - F1: 0.5453
sub_18:Test (Best Model) - Loss: 1.2229 - Accuracy: 0.4706 - F1: 0.3750
sub_17:Test (Best Model) - Loss: 1.0472 - Accuracy: 0.5588 - F1: 0.5324
sub_27:Test (Best Model) - Loss: 1.0472 - Accuracy: 0.5588 - F1: 0.5324
sub_22:Test (Best Model) - Loss: 1.0765 - Accuracy: 0.5147 - F1: 0.4850
sub_16:Test (Best Model) - Loss: 0.9815 - Accuracy: 0.6029 - F1: 0.6046
sub_8:Test (Best Model) - Loss: 1.0613 - Accuracy: 0.6176 - F1: 0.5905
sub_24:Test (Best Model) - Loss: 0.7345 - Accuracy: 0.7206 - F1: 0.7375
sub_11:Test (Best Model) - Loss: 0.9325 - Accuracy: 0.6667 - F1: 0.6482
sub_7:Test (Best Model) - Loss: 1.1708 - Accuracy: 0.4265 - F1: 0.4696
sub_23:Test (Best Model) - Loss: 1.4637 - Accuracy: 0.5217 - F1: 0.4832
sub_9:Test (Best Model) - Loss: 1.1250 - Accuracy: 0.4706 - F1: 0.4451
sub_4:Test (Best Model) - Loss: 0.8726 - Accuracy: 0.7536 - F1: 0.7169
sub_15:Test (Best Model) - Loss: 1.2613 - Accuracy: 0.5147 - F1: 0.4106
sub_6:Test (Best Model) - Loss: 0.8009 - Accuracy: 0.7391 - F1: 0.7288
sub_13:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3529 - F1: 0.2928
sub_18:Test (Best Model) - Loss: 0.9986 - Accuracy: 0.5588 - F1: 0.5313
sub_26:Test (Best Model) - Loss: 1.0031 - Accuracy: 0.4412 - F1: 0.4579
sub_28:Test (Best Model) - Loss: 1.7334 - Accuracy: 0.3824 - F1: 0.2950
sub_14:Test (Best Model) - Loss: 0.9311 - Accuracy: 0.6765 - F1: 0.6765
sub_25:Test (Best Model) - Loss: 0.7936 - Accuracy: 0.6471 - F1: 0.6665
sub_2:Test (Best Model) - Loss: 0.9125 - Accuracy: 0.7101 - F1: 0.6934
sub_3:Test (Best Model) - Loss: 1.0387 - Accuracy: 0.5797 - F1: 0.5467
sub_10:Test (Best Model) - Loss: 0.7308 - Accuracy: 0.7681 - F1: 0.7584
sub_19:Test (Best Model) - Loss: 0.8388 - Accuracy: 0.7206 - F1: 0.7225
sub_5:Test (Best Model) - Loss: 0.7571 - Accuracy: 0.7794 - F1: 0.7513
sub_20:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.6812 - F1: 0.6583
sub_12:Test (Best Model) - Loss: 0.8679 - Accuracy: 0.6471 - F1: 0.6379
sub_22:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.4706 - F1: 0.4581
sub_17:Test (Best Model) - Loss: 0.8865 - Accuracy: 0.5441 - F1: 0.5073
sub_27:Test (Best Model) - Loss: 0.8865 - Accuracy: 0.5441 - F1: 0.5073
sub_29:Test (Best Model) - Loss: 0.8082 - Accuracy: 0.6377 - F1: 0.5819
sub_21:Test (Best Model) - Loss: 0.9438 - Accuracy: 0.7206 - F1: 0.6507
sub_1:Test (Best Model) - Loss: 1.0843 - Accuracy: 0.5441 - F1: 0.5137
sub_16:Test (Best Model) - Loss: 0.9202 - Accuracy: 0.7059 - F1: 0.7048
sub_9:Test (Best Model) - Loss: 1.2903 - Accuracy: 0.3971 - F1: 0.4276
sub_4:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.7681 - F1: 0.7668
sub_7:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.7500 - F1: 0.7407
sub_8:Test (Best Model) - Loss: 0.7921 - Accuracy: 0.6618 - F1: 0.6477
sub_24:Test (Best Model) - Loss: 1.0850 - Accuracy: 0.5294 - F1: 0.4750
sub_23:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.3913 - F1: 0.3334
sub_13:Test (Best Model) - Loss: 1.5449 - Accuracy: 0.3824 - F1: 0.3151
sub_11:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.7536 - F1: 0.7566
sub_6:Test (Best Model) - Loss: 0.9759 - Accuracy: 0.5797 - F1: 0.5579
sub_18:Test (Best Model) - Loss: 0.8555 - Accuracy: 0.6324 - F1: 0.5905
sub_25:Test (Best Model) - Loss: 0.9844 - Accuracy: 0.6471 - F1: 0.5997
sub_5:Test (Best Model) - Loss: 1.0291 - Accuracy: 0.6324 - F1: 0.5603
sub_28:Test (Best Model) - Loss: 1.4729 - Accuracy: 0.3382 - F1: 0.2477
sub_19:Test (Best Model) - Loss: 1.0743 - Accuracy: 0.4706 - F1: 0.4106
sub_10:Test (Best Model) - Loss: 0.9189 - Accuracy: 0.5942 - F1: 0.5751
sub_12:Test (Best Model) - Loss: 0.9657 - Accuracy: 0.5735 - F1: 0.5092
sub_3:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.7536 - F1: 0.7621
sub_14:Test (Best Model) - Loss: 0.9851 - Accuracy: 0.6029 - F1: 0.5970
sub_2:Test (Best Model) - Loss: 0.9544 - Accuracy: 0.5652 - F1: 0.5142
sub_29:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.4783 - F1: 0.3945
sub_22:Test (Best Model) - Loss: 0.9537 - Accuracy: 0.5588 - F1: 0.5374
sub_21:Test (Best Model) - Loss: 0.8793 - Accuracy: 0.5294 - F1: 0.4529
sub_15:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.5294 - F1: 0.4408
sub_20:Test (Best Model) - Loss: 0.7596 - Accuracy: 0.6377 - F1: 0.6297
sub_7:Test (Best Model) - Loss: 0.7299 - Accuracy: 0.7941 - F1: 0.7914
sub_17:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.7794 - F1: 0.7805
sub_9:Test (Best Model) - Loss: 0.9757 - Accuracy: 0.5882 - F1: 0.5777
sub_26:Test (Best Model) - Loss: 0.8553 - Accuracy: 0.6029 - F1: 0.6284
sub_27:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.7794 - F1: 0.7805
sub_24:Test (Best Model) - Loss: 1.1515 - Accuracy: 0.2500 - F1: 0.2996
sub_4:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.7246 - F1: 0.6770
sub_16:Test (Best Model) - Loss: 0.5387 - Accuracy: 0.8529 - F1: 0.8516
sub_6:Test (Best Model) - Loss: 0.7550 - Accuracy: 0.6957 - F1: 0.6743
sub_2:Test (Best Model) - Loss: 1.0108 - Accuracy: 0.6232 - F1: 0.5958
sub_8:Test (Best Model) - Loss: 0.7192 - Accuracy: 0.7206 - F1: 0.7360
sub_14:Test (Best Model) - Loss: 0.9886 - Accuracy: 0.5588 - F1: 0.5425
sub_1:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.7206 - F1: 0.6748
sub_11:Test (Best Model) - Loss: 0.8350 - Accuracy: 0.6522 - F1: 0.6427
sub_12:Test (Best Model) - Loss: 0.7992 - Accuracy: 0.7206 - F1: 0.7346
sub_23:Test (Best Model) - Loss: 1.1464 - Accuracy: 0.5507 - F1: 0.5045
sub_22:Test (Best Model) - Loss: 1.1724 - Accuracy: 0.3529 - F1: 0.3872
sub_5:Test (Best Model) - Loss: 1.2607 - Accuracy: 0.5147 - F1: 0.4157
sub_25:Test (Best Model) - Loss: 0.5881 - Accuracy: 0.7353 - F1: 0.7347
sub_18:Test (Best Model) - Loss: 1.0767 - Accuracy: 0.4412 - F1: 0.3659
sub_28:Test (Best Model) - Loss: 1.1502 - Accuracy: 0.4853 - F1: 0.4032
sub_13:Test (Best Model) - Loss: 1.3363 - Accuracy: 0.3088 - F1: 0.2391
sub_20:Test (Best Model) - Loss: 0.7318 - Accuracy: 0.7246 - F1: 0.7245
sub_15:Test (Best Model) - Loss: 0.8671 - Accuracy: 0.6029 - F1: 0.5746
sub_24:Test (Best Model) - Loss: 0.8344 - Accuracy: 0.7059 - F1: 0.6912
sub_21:Test (Best Model) - Loss: 0.4848 - Accuracy: 0.8382 - F1: 0.8366
sub_29:Test (Best Model) - Loss: 0.9781 - Accuracy: 0.6087 - F1: 0.5905
sub_6:Test (Best Model) - Loss: 0.8903 - Accuracy: 0.5507 - F1: 0.5327
sub_14:Test (Best Model) - Loss: 1.1848 - Accuracy: 0.4559 - F1: 0.4280
sub_16:Test (Best Model) - Loss: 0.8571 - Accuracy: 0.6471 - F1: 0.5859
sub_3:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.6667 - F1: 0.6295
sub_17:Test (Best Model) - Loss: 0.8013 - Accuracy: 0.6471 - F1: 0.5999
sub_9:Test (Best Model) - Loss: 1.0722 - Accuracy: 0.4412 - F1: 0.3856
sub_23:Test (Best Model) - Loss: 1.2154 - Accuracy: 0.4783 - F1: 0.4452
sub_27:Test (Best Model) - Loss: 0.8013 - Accuracy: 0.6471 - F1: 0.5999
sub_12:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.7206 - F1: 0.7370
sub_18:Test (Best Model) - Loss: 0.8856 - Accuracy: 0.5441 - F1: 0.5037
sub_28:Test (Best Model) - Loss: 1.8354 - Accuracy: 0.2647 - F1: 0.2097
sub_11:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.6667 - F1: 0.6478
sub_21:Test (Best Model) - Loss: 0.8415 - Accuracy: 0.6765 - F1: 0.6740
sub_25:Test (Best Model) - Loss: 0.9580 - Accuracy: 0.4706 - F1: 0.4498
sub_1:Test (Best Model) - Loss: 0.9759 - Accuracy: 0.6324 - F1: 0.5862
sub_15:Test (Best Model) - Loss: 1.0651 - Accuracy: 0.5441 - F1: 0.4473
sub_29:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.7536 - F1: 0.7509
sub_13:Test (Best Model) - Loss: 1.0392 - Accuracy: 0.4706 - F1: 0.4311
sub_9:Test (Best Model) - Loss: 0.8342 - Accuracy: 0.6618 - F1: 0.6663
sub_1:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.7206 - F1: 0.6648
sub_13:Test (Best Model) - Loss: 1.1980 - Accuracy: 0.4853 - F1: 0.4464
sub_29:Test (Best Model) - Loss: 0.8013 - Accuracy: 0.6087 - F1: 0.6147

=== Summary Results ===

acc: 60.98 ± 8.31
F1: 58.20 ± 9.11
acc-in: 89.56 ± 3.47
F1-in: 89.12 ± 3.78
