lr: 0.0001
sub_10:Test (Best Model) - Loss: 1.1530 - Accuracy: 0.5147 - F1: 0.5001
sub_7:Test (Best Model) - Loss: 0.1975 - Accuracy: 0.9265 - F1: 0.9179
sub_4:Test (Best Model) - Loss: 0.8133 - Accuracy: 0.6812 - F1: 0.6387
sub_12:Test (Best Model) - Loss: 0.9249 - Accuracy: 0.6324 - F1: 0.6395
sub_11:Test (Best Model) - Loss: 0.9499 - Accuracy: 0.6667 - F1: 0.6359
sub_3:Test (Best Model) - Loss: 1.1655 - Accuracy: 0.7206 - F1: 0.6948
sub_16:Test (Best Model) - Loss: 1.0172 - Accuracy: 0.7353 - F1: 0.7188
sub_22:Test (Best Model) - Loss: 2.3919 - Accuracy: 0.4559 - F1: 0.4338
sub_14:Test (Best Model) - Loss: 2.2180 - Accuracy: 0.4853 - F1: 0.4148
sub_21:Test (Best Model) - Loss: 0.3058 - Accuracy: 0.9118 - F1: 0.9074
sub_2:Test (Best Model) - Loss: 0.9741 - Accuracy: 0.6957 - F1: 0.6645
sub_6:Test (Best Model) - Loss: 1.9015 - Accuracy: 0.5588 - F1: 0.5064
sub_17:Test (Best Model) - Loss: 0.3211 - Accuracy: 0.8986 - F1: 0.8992
sub_27:Test (Best Model) - Loss: 0.3211 - Accuracy: 0.8986 - F1: 0.8992
sub_19:Test (Best Model) - Loss: 4.4225 - Accuracy: 0.4118 - F1: 0.3394
sub_29:Test (Best Model) - Loss: 2.0825 - Accuracy: 0.6029 - F1: 0.5733
sub_23:Test (Best Model) - Loss: 0.5171 - Accuracy: 0.8696 - F1: 0.8749
sub_26:Test (Best Model) - Loss: 1.6288 - Accuracy: 0.6232 - F1: 0.6295
sub_8:Test (Best Model) - Loss: 2.8322 - Accuracy: 0.6324 - F1: 0.6004
sub_9:Test (Best Model) - Loss: 0.4496 - Accuracy: 0.7794 - F1: 0.7911
sub_5:Test (Best Model) - Loss: 2.8326 - Accuracy: 0.5147 - F1: 0.4519
sub_1:Test (Best Model) - Loss: 2.3903 - Accuracy: 0.5147 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 2.6291 - Accuracy: 0.4265 - F1: 0.3366
sub_18:Test (Best Model) - Loss: 0.8968 - Accuracy: 0.6667 - F1: 0.6595
sub_24:Test (Best Model) - Loss: 1.8020 - Accuracy: 0.6471 - F1: 0.5955
sub_25:Test (Best Model) - Loss: 0.0490 - Accuracy: 0.9855 - F1: 0.9846
sub_13:Test (Best Model) - Loss: 3.3736 - Accuracy: 0.4706 - F1: 0.3700
sub_7:Test (Best Model) - Loss: 0.3109 - Accuracy: 0.8529 - F1: 0.8351
sub_3:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.7941 - F1: 0.7973
sub_11:Test (Best Model) - Loss: 1.7283 - Accuracy: 0.5942 - F1: 0.5487
sub_16:Test (Best Model) - Loss: 1.4024 - Accuracy: 0.6618 - F1: 0.6447
sub_6:Test (Best Model) - Loss: 2.8882 - Accuracy: 0.4559 - F1: 0.3813
sub_15:Test (Best Model) - Loss: 1.4254 - Accuracy: 0.6176 - F1: 0.6225
sub_20:Test (Best Model) - Loss: 1.2998 - Accuracy: 0.7647 - F1: 0.7231
sub_4:Test (Best Model) - Loss: 1.7587 - Accuracy: 0.6667 - F1: 0.6215
sub_10:Test (Best Model) - Loss: 2.7580 - Accuracy: 0.5000 - F1: 0.5152
sub_26:Test (Best Model) - Loss: 0.9844 - Accuracy: 0.7391 - F1: 0.7500
sub_8:Test (Best Model) - Loss: 1.6311 - Accuracy: 0.6912 - F1: 0.6118
sub_22:Test (Best Model) - Loss: 1.9110 - Accuracy: 0.5735 - F1: 0.5239
sub_14:Test (Best Model) - Loss: 3.0165 - Accuracy: 0.4706 - F1: 0.3768
sub_9:Test (Best Model) - Loss: 1.0119 - Accuracy: 0.6324 - F1: 0.6577
sub_21:Test (Best Model) - Loss: 0.4796 - Accuracy: 0.8088 - F1: 0.8029
sub_5:Test (Best Model) - Loss: 2.3789 - Accuracy: 0.5441 - F1: 0.5233
sub_1:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.6176 - F1: 0.5955
sub_12:Test (Best Model) - Loss: 2.3552 - Accuracy: 0.7206 - F1: 0.6495
sub_29:Test (Best Model) - Loss: 1.4857 - Accuracy: 0.5147 - F1: 0.5505
sub_19:Test (Best Model) - Loss: 4.2119 - Accuracy: 0.3529 - F1: 0.3241
sub_3:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.8088 - F1: 0.8080
sub_24:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.5735 - F1: 0.5306
sub_25:Test (Best Model) - Loss: 0.2033 - Accuracy: 0.9420 - F1: 0.9437
sub_18:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.7681 - F1: 0.7750
sub_28:Test (Best Model) - Loss: 1.6352 - Accuracy: 0.6029 - F1: 0.5216
sub_27:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.7246 - F1: 0.7198
sub_7:Test (Best Model) - Loss: 0.3162 - Accuracy: 0.8676 - F1: 0.8559
sub_2:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.6667 - F1: 0.6149
sub_16:Test (Best Model) - Loss: 1.0127 - Accuracy: 0.7353 - F1: 0.7009
sub_23:Test (Best Model) - Loss: 1.6746 - Accuracy: 0.6667 - F1: 0.6601
sub_17:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.7246 - F1: 0.7198
sub_20:Test (Best Model) - Loss: 1.1456 - Accuracy: 0.7059 - F1: 0.6571
sub_11:Test (Best Model) - Loss: 0.9207 - Accuracy: 0.7391 - F1: 0.6917
sub_8:Test (Best Model) - Loss: 1.4754 - Accuracy: 0.5882 - F1: 0.5596
sub_15:Test (Best Model) - Loss: 1.1252 - Accuracy: 0.6324 - F1: 0.6301
sub_6:Test (Best Model) - Loss: 1.7052 - Accuracy: 0.5000 - F1: 0.4641
sub_26:Test (Best Model) - Loss: 1.1394 - Accuracy: 0.5942 - F1: 0.5858
sub_5:Test (Best Model) - Loss: 2.9402 - Accuracy: 0.4853 - F1: 0.4031
sub_4:Test (Best Model) - Loss: 1.6904 - Accuracy: 0.6812 - F1: 0.6312
sub_13:Test (Best Model) - Loss: 1.4967 - Accuracy: 0.6029 - F1: 0.5467
sub_10:Test (Best Model) - Loss: 2.8839 - Accuracy: 0.4118 - F1: 0.4131
sub_19:Test (Best Model) - Loss: 3.0437 - Accuracy: 0.4412 - F1: 0.3643
sub_14:Test (Best Model) - Loss: 3.4878 - Accuracy: 0.4706 - F1: 0.3750
sub_1:Test (Best Model) - Loss: 2.0409 - Accuracy: 0.5441 - F1: 0.5330
sub_22:Test (Best Model) - Loss: 2.1598 - Accuracy: 0.5735 - F1: 0.5425
sub_9:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.7794 - F1: 0.7866
sub_21:Test (Best Model) - Loss: 0.3215 - Accuracy: 0.9118 - F1: 0.9067
sub_12:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.7059 - F1: 0.6432
sub_29:Test (Best Model) - Loss: 1.4284 - Accuracy: 0.4853 - F1: 0.5296
sub_25:Test (Best Model) - Loss: 0.0813 - Accuracy: 0.9855 - F1: 0.9846
sub_11:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.7826 - F1: 0.7654
sub_24:Test (Best Model) - Loss: 2.0106 - Accuracy: 0.5735 - F1: 0.5610
sub_20:Test (Best Model) - Loss: 1.7844 - Accuracy: 0.5882 - F1: 0.5301
sub_18:Test (Best Model) - Loss: 1.3234 - Accuracy: 0.7101 - F1: 0.6915
sub_7:Test (Best Model) - Loss: 0.1868 - Accuracy: 0.9412 - F1: 0.9426
sub_16:Test (Best Model) - Loss: 0.8337 - Accuracy: 0.7353 - F1: 0.7388
sub_3:Test (Best Model) - Loss: 0.5820 - Accuracy: 0.8676 - F1: 0.8662
sub_6:Test (Best Model) - Loss: 2.8010 - Accuracy: 0.4412 - F1: 0.3845
sub_5:Test (Best Model) - Loss: 1.9802 - Accuracy: 0.4853 - F1: 0.4245
sub_4:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.6667 - F1: 0.6256
sub_8:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.6765 - F1: 0.6158
sub_26:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.7101 - F1: 0.7162
sub_10:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.5588 - F1: 0.5526
sub_23:Test (Best Model) - Loss: 1.5775 - Accuracy: 0.7826 - F1: 0.7403
sub_28:Test (Best Model) - Loss: 2.5069 - Accuracy: 0.4853 - F1: 0.4290
sub_14:Test (Best Model) - Loss: 3.5635 - Accuracy: 0.4706 - F1: 0.3768
sub_2:Test (Best Model) - Loss: 2.2157 - Accuracy: 0.5942 - F1: 0.5567
sub_15:Test (Best Model) - Loss: 1.1020 - Accuracy: 0.7206 - F1: 0.7152
sub_17:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.8261 - F1: 0.8276
sub_25:Test (Best Model) - Loss: 0.0929 - Accuracy: 0.9855 - F1: 0.9846
sub_27:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.8261 - F1: 0.8276
sub_9:Test (Best Model) - Loss: 0.5542 - Accuracy: 0.7941 - F1: 0.8013
sub_21:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.8676 - F1: 0.8607
sub_19:Test (Best Model) - Loss: 4.2082 - Accuracy: 0.3824 - F1: 0.3409
sub_11:Test (Best Model) - Loss: 0.8785 - Accuracy: 0.7101 - F1: 0.7078
sub_3:Test (Best Model) - Loss: 0.5398 - Accuracy: 0.8382 - F1: 0.8364
sub_13:Test (Best Model) - Loss: 3.4125 - Accuracy: 0.4853 - F1: 0.4031
sub_22:Test (Best Model) - Loss: 2.5094 - Accuracy: 0.5882 - F1: 0.5345
sub_4:Test (Best Model) - Loss: 0.8645 - Accuracy: 0.6812 - F1: 0.6312
sub_18:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.7391 - F1: 0.7212
sub_1:Test (Best Model) - Loss: 1.6863 - Accuracy: 0.5441 - F1: 0.5320
sub_24:Test (Best Model) - Loss: 1.2999 - Accuracy: 0.7059 - F1: 0.7044
sub_5:Test (Best Model) - Loss: 2.3570 - Accuracy: 0.5147 - F1: 0.4519
sub_16:Test (Best Model) - Loss: 0.9602 - Accuracy: 0.7206 - F1: 0.7272
sub_7:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.7941 - F1: 0.7804
sub_12:Test (Best Model) - Loss: 1.7443 - Accuracy: 0.7206 - F1: 0.6479
sub_20:Test (Best Model) - Loss: 1.9340 - Accuracy: 0.5882 - F1: 0.5345
sub_23:Test (Best Model) - Loss: 0.7342 - Accuracy: 0.8406 - F1: 0.8252
sub_29:Test (Best Model) - Loss: 1.6796 - Accuracy: 0.6471 - F1: 0.6199
sub_2:Test (Best Model) - Loss: 1.9348 - Accuracy: 0.4928 - F1: 0.4586
sub_8:Test (Best Model) - Loss: 2.5776 - Accuracy: 0.6471 - F1: 0.6072
sub_26:Test (Best Model) - Loss: 0.6255 - Accuracy: 0.7971 - F1: 0.8097
sub_10:Test (Best Model) - Loss: 2.8301 - Accuracy: 0.4265 - F1: 0.4352
sub_25:Test (Best Model) - Loss: 0.1178 - Accuracy: 0.9855 - F1: 0.9846
sub_28:Test (Best Model) - Loss: 1.7488 - Accuracy: 0.7059 - F1: 0.6113
sub_17:Test (Best Model) - Loss: 0.7504 - Accuracy: 0.7971 - F1: 0.7989
sub_5:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.7206 - F1: 0.6450
sub_22:Test (Best Model) - Loss: 2.4090 - Accuracy: 0.5000 - F1: 0.4598
sub_11:Test (Best Model) - Loss: 1.6523 - Accuracy: 0.7391 - F1: 0.6882
sub_27:Test (Best Model) - Loss: 0.7504 - Accuracy: 0.7971 - F1: 0.7989
sub_3:Test (Best Model) - Loss: 2.4269 - Accuracy: 0.6377 - F1: 0.6112
sub_21:Test (Best Model) - Loss: 0.5007 - Accuracy: 0.8824 - F1: 0.8824
sub_19:Test (Best Model) - Loss: 4.8804 - Accuracy: 0.3676 - F1: 0.3186
sub_15:Test (Best Model) - Loss: 0.9572 - Accuracy: 0.7206 - F1: 0.7192
sub_18:Test (Best Model) - Loss: 0.7337 - Accuracy: 0.6957 - F1: 0.6911
sub_6:Test (Best Model) - Loss: 3.4793 - Accuracy: 0.4265 - F1: 0.3661
sub_12:Test (Best Model) - Loss: 0.8784 - Accuracy: 0.7059 - F1: 0.6631
sub_14:Test (Best Model) - Loss: 4.4915 - Accuracy: 0.4706 - F1: 0.3975
sub_7:Test (Best Model) - Loss: 1.5979 - Accuracy: 0.7059 - F1: 0.6210
sub_9:Test (Best Model) - Loss: 0.8355 - Accuracy: 0.7647 - F1: 0.7837
sub_24:Test (Best Model) - Loss: 1.8649 - Accuracy: 0.5147 - F1: 0.5032
sub_4:Test (Best Model) - Loss: 1.2132 - Accuracy: 0.7826 - F1: 0.7447
sub_23:Test (Best Model) - Loss: 1.0103 - Accuracy: 0.6667 - F1: 0.6704
sub_13:Test (Best Model) - Loss: 2.9552 - Accuracy: 0.5147 - F1: 0.4495
sub_29:Test (Best Model) - Loss: 2.7331 - Accuracy: 0.5000 - F1: 0.5073
sub_25:Test (Best Model) - Loss: 1.6936 - Accuracy: 0.7353 - F1: 0.6917
sub_26:Test (Best Model) - Loss: 2.2091 - Accuracy: 0.5441 - F1: 0.5278
sub_20:Test (Best Model) - Loss: 1.8764 - Accuracy: 0.7059 - F1: 0.6679
sub_10:Test (Best Model) - Loss: 1.4687 - Accuracy: 0.5147 - F1: 0.4907
sub_1:Test (Best Model) - Loss: 4.0171 - Accuracy: 0.4706 - F1: 0.4184
sub_22:Test (Best Model) - Loss: 2.4227 - Accuracy: 0.5652 - F1: 0.5208
sub_28:Test (Best Model) - Loss: 2.0796 - Accuracy: 0.4853 - F1: 0.3792
sub_27:Test (Best Model) - Loss: 0.5703 - Accuracy: 0.8261 - F1: 0.8307
sub_8:Test (Best Model) - Loss: 2.1130 - Accuracy: 0.7206 - F1: 0.6528
sub_5:Test (Best Model) - Loss: 0.9950 - Accuracy: 0.6912 - F1: 0.6352
sub_17:Test (Best Model) - Loss: 0.5703 - Accuracy: 0.8261 - F1: 0.8307
sub_14:Test (Best Model) - Loss: 1.6007 - Accuracy: 0.4559 - F1: 0.4483
sub_21:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.8382 - F1: 0.8343
sub_6:Test (Best Model) - Loss: 2.0532 - Accuracy: 0.5652 - F1: 0.5020
sub_7:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.7059 - F1: 0.6129
sub_3:Test (Best Model) - Loss: 1.7246 - Accuracy: 0.6812 - F1: 0.6354
sub_2:Test (Best Model) - Loss: 1.0363 - Accuracy: 0.6087 - F1: 0.5649
sub_4:Test (Best Model) - Loss: 0.4597 - Accuracy: 0.7826 - F1: 0.7518
sub_11:Test (Best Model) - Loss: 1.4119 - Accuracy: 0.7101 - F1: 0.6686
sub_16:Test (Best Model) - Loss: 1.0718 - Accuracy: 0.7353 - F1: 0.7425
sub_18:Test (Best Model) - Loss: 2.4917 - Accuracy: 0.4265 - F1: 0.4839
sub_15:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.5882 - F1: 0.5643
sub_24:Test (Best Model) - Loss: 1.6953 - Accuracy: 0.7206 - F1: 0.6451
sub_19:Test (Best Model) - Loss: 2.5269 - Accuracy: 0.6471 - F1: 0.6475
sub_10:Test (Best Model) - Loss: 1.2623 - Accuracy: 0.3529 - F1: 0.3046
sub_25:Test (Best Model) - Loss: 1.2783 - Accuracy: 0.7206 - F1: 0.6648
sub_12:Test (Best Model) - Loss: 1.1079 - Accuracy: 0.7391 - F1: 0.7497
sub_14:Test (Best Model) - Loss: 0.8512 - Accuracy: 0.5000 - F1: 0.4566
sub_13:Test (Best Model) - Loss: 3.0637 - Accuracy: 0.4412 - F1: 0.3524
sub_23:Test (Best Model) - Loss: 1.0548 - Accuracy: 0.6471 - F1: 0.6344
sub_9:Test (Best Model) - Loss: 2.8986 - Accuracy: 0.4853 - F1: 0.4037
sub_22:Test (Best Model) - Loss: 2.1036 - Accuracy: 0.5217 - F1: 0.4519
sub_8:Test (Best Model) - Loss: 1.5357 - Accuracy: 0.7206 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 2.4649 - Accuracy: 0.7206 - F1: 0.6495
sub_11:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7826 - F1: 0.7754
sub_27:Test (Best Model) - Loss: 2.1610 - Accuracy: 0.6377 - F1: 0.6047
sub_17:Test (Best Model) - Loss: 2.1610 - Accuracy: 0.6377 - F1: 0.6047
sub_29:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.8235 - F1: 0.8125
sub_5:Test (Best Model) - Loss: 1.5009 - Accuracy: 0.6176 - F1: 0.5737
sub_1:Test (Best Model) - Loss: 0.9895 - Accuracy: 0.7101 - F1: 0.7082
sub_28:Test (Best Model) - Loss: 4.4896 - Accuracy: 0.4412 - F1: 0.3429
sub_4:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.8116 - F1: 0.7894
sub_18:Test (Best Model) - Loss: 1.1157 - Accuracy: 0.6176 - F1: 0.6201
sub_2:Test (Best Model) - Loss: 0.9812 - Accuracy: 0.7647 - F1: 0.7319
sub_7:Test (Best Model) - Loss: 2.6225 - Accuracy: 0.5882 - F1: 0.5047
sub_6:Test (Best Model) - Loss: 0.8344 - Accuracy: 0.6957 - F1: 0.6594
sub_16:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.7794 - F1: 0.7807
sub_26:Test (Best Model) - Loss: 3.5473 - Accuracy: 0.4118 - F1: 0.3869
sub_10:Test (Best Model) - Loss: 1.4291 - Accuracy: 0.4118 - F1: 0.2990
sub_14:Test (Best Model) - Loss: 1.7092 - Accuracy: 0.4706 - F1: 0.3666
sub_22:Test (Best Model) - Loss: 2.1746 - Accuracy: 0.5362 - F1: 0.4836
sub_19:Test (Best Model) - Loss: 1.4397 - Accuracy: 0.6912 - F1: 0.6861
sub_25:Test (Best Model) - Loss: 1.2530 - Accuracy: 0.7353 - F1: 0.7033
sub_3:Test (Best Model) - Loss: 3.3343 - Accuracy: 0.6377 - F1: 0.5993
sub_23:Test (Best Model) - Loss: 1.2935 - Accuracy: 0.3824 - F1: 0.3309
sub_9:Test (Best Model) - Loss: 0.7708 - Accuracy: 0.5147 - F1: 0.4712
sub_24:Test (Best Model) - Loss: 1.8988 - Accuracy: 0.7059 - F1: 0.6255
sub_28:Test (Best Model) - Loss: 1.9951 - Accuracy: 0.4412 - F1: 0.3558
sub_5:Test (Best Model) - Loss: 0.2528 - Accuracy: 0.9265 - F1: 0.9223
sub_21:Test (Best Model) - Loss: 0.1896 - Accuracy: 0.8971 - F1: 0.8945
sub_8:Test (Best Model) - Loss: 2.2162 - Accuracy: 0.7206 - F1: 0.6528
sub_12:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.7391 - F1: 0.7131
sub_26:Test (Best Model) - Loss: 1.7581 - Accuracy: 0.4559 - F1: 0.4247
sub_7:Test (Best Model) - Loss: 1.1608 - Accuracy: 0.7353 - F1: 0.6631
sub_2:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.7500 - F1: 0.7222
sub_15:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.8382 - F1: 0.8373
sub_18:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.6029 - F1: 0.5815
sub_4:Test (Best Model) - Loss: 0.2772 - Accuracy: 0.8841 - F1: 0.8877
sub_20:Test (Best Model) - Loss: 1.2678 - Accuracy: 0.7206 - F1: 0.6479
sub_13:Test (Best Model) - Loss: 2.5123 - Accuracy: 0.5362 - F1: 0.4682
sub_16:Test (Best Model) - Loss: 0.4821 - Accuracy: 0.8235 - F1: 0.8217
sub_11:Test (Best Model) - Loss: 1.7632 - Accuracy: 0.6957 - F1: 0.6437
sub_25:Test (Best Model) - Loss: 1.1832 - Accuracy: 0.7941 - F1: 0.7790
sub_14:Test (Best Model) - Loss: 2.6018 - Accuracy: 0.4118 - F1: 0.3833
sub_27:Test (Best Model) - Loss: 1.8351 - Accuracy: 0.5362 - F1: 0.4950
sub_29:Test (Best Model) - Loss: 0.1964 - Accuracy: 0.9265 - F1: 0.9292
sub_17:Test (Best Model) - Loss: 1.8351 - Accuracy: 0.5362 - F1: 0.4950
sub_9:Test (Best Model) - Loss: 1.4044 - Accuracy: 0.5441 - F1: 0.4806
sub_8:Test (Best Model) - Loss: 0.5404 - Accuracy: 0.7353 - F1: 0.6927
sub_10:Test (Best Model) - Loss: 2.0467 - Accuracy: 0.5294 - F1: 0.5110
sub_6:Test (Best Model) - Loss: 2.7896 - Accuracy: 0.4348 - F1: 0.3198
sub_22:Test (Best Model) - Loss: 2.7100 - Accuracy: 0.5217 - F1: 0.4910
sub_26:Test (Best Model) - Loss: 1.2172 - Accuracy: 0.6324 - F1: 0.5632
sub_19:Test (Best Model) - Loss: 0.8716 - Accuracy: 0.6912 - F1: 0.7193
sub_28:Test (Best Model) - Loss: 1.7698 - Accuracy: 0.3824 - F1: 0.3234
sub_24:Test (Best Model) - Loss: 1.5780 - Accuracy: 0.7059 - F1: 0.6220
sub_1:Test (Best Model) - Loss: 1.1301 - Accuracy: 0.6667 - F1: 0.6514
sub_3:Test (Best Model) - Loss: 2.1912 - Accuracy: 0.6667 - F1: 0.6176
sub_2:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.8088 - F1: 0.8129
sub_4:Test (Best Model) - Loss: 0.4590 - Accuracy: 0.8261 - F1: 0.8084
sub_25:Test (Best Model) - Loss: 1.2398 - Accuracy: 0.7500 - F1: 0.6961
sub_21:Test (Best Model) - Loss: 0.9271 - Accuracy: 0.7941 - F1: 0.7801
sub_11:Test (Best Model) - Loss: 1.0466 - Accuracy: 0.7246 - F1: 0.6959
sub_6:Test (Best Model) - Loss: 0.5587 - Accuracy: 0.7826 - F1: 0.7790
sub_18:Test (Best Model) - Loss: 1.6922 - Accuracy: 0.6471 - F1: 0.5990
sub_23:Test (Best Model) - Loss: 2.9003 - Accuracy: 0.4706 - F1: 0.3366
sub_7:Test (Best Model) - Loss: 1.7524 - Accuracy: 0.6912 - F1: 0.6162
sub_12:Test (Best Model) - Loss: 0.8977 - Accuracy: 0.7681 - F1: 0.7450
sub_16:Test (Best Model) - Loss: 0.7638 - Accuracy: 0.7500 - F1: 0.7547
sub_5:Test (Best Model) - Loss: 0.9331 - Accuracy: 0.7059 - F1: 0.6586
sub_20:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.7059 - F1: 0.6326
sub_13:Test (Best Model) - Loss: 1.7879 - Accuracy: 0.4348 - F1: 0.3011
sub_8:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.8529 - F1: 0.8600
sub_10:Test (Best Model) - Loss: 1.5506 - Accuracy: 0.5000 - F1: 0.4781
sub_14:Test (Best Model) - Loss: 2.7412 - Accuracy: 0.3676 - F1: 0.3939
sub_22:Test (Best Model) - Loss: 2.5079 - Accuracy: 0.4203 - F1: 0.3556
sub_27:Test (Best Model) - Loss: 1.1222 - Accuracy: 0.5942 - F1: 0.5636
sub_15:Test (Best Model) - Loss: 0.8158 - Accuracy: 0.7941 - F1: 0.7881
sub_28:Test (Best Model) - Loss: 3.9834 - Accuracy: 0.4412 - F1: 0.3558
sub_24:Test (Best Model) - Loss: 1.1625 - Accuracy: 0.7206 - F1: 0.6368
sub_17:Test (Best Model) - Loss: 1.1222 - Accuracy: 0.5942 - F1: 0.5636
sub_29:Test (Best Model) - Loss: 1.1275 - Accuracy: 0.7647 - F1: 0.7231
sub_9:Test (Best Model) - Loss: 2.3000 - Accuracy: 0.5441 - F1: 0.4883
sub_1:Test (Best Model) - Loss: 1.2510 - Accuracy: 0.6087 - F1: 0.5835
sub_26:Test (Best Model) - Loss: 3.3941 - Accuracy: 0.3382 - F1: 0.3110
sub_2:Test (Best Model) - Loss: 0.7921 - Accuracy: 0.7206 - F1: 0.7072
sub_3:Test (Best Model) - Loss: 1.9379 - Accuracy: 0.6812 - F1: 0.6324
sub_16:Test (Best Model) - Loss: 1.2142 - Accuracy: 0.5588 - F1: 0.5104
sub_21:Test (Best Model) - Loss: 0.4165 - Accuracy: 0.8382 - F1: 0.8323
sub_25:Test (Best Model) - Loss: 1.7300 - Accuracy: 0.7206 - F1: 0.6925
sub_18:Test (Best Model) - Loss: 1.3136 - Accuracy: 0.5294 - F1: 0.5556
sub_4:Test (Best Model) - Loss: 1.2297 - Accuracy: 0.7826 - F1: 0.7479
sub_14:Test (Best Model) - Loss: 0.5447 - Accuracy: 0.7206 - F1: 0.7208
sub_19:Test (Best Model) - Loss: 1.8508 - Accuracy: 0.7206 - F1: 0.7315
sub_24:Test (Best Model) - Loss: 1.1421 - Accuracy: 0.7059 - F1: 0.6287
sub_22:Test (Best Model) - Loss: 2.1932 - Accuracy: 0.4706 - F1: 0.4422
sub_23:Test (Best Model) - Loss: 1.8281 - Accuracy: 0.5441 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 1.8712 - Accuracy: 0.6765 - F1: 0.6460
sub_11:Test (Best Model) - Loss: 0.7298 - Accuracy: 0.7536 - F1: 0.7320
sub_10:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.5797 - F1: 0.5160
sub_7:Test (Best Model) - Loss: 2.3300 - Accuracy: 0.5588 - F1: 0.4806
sub_13:Test (Best Model) - Loss: 1.5816 - Accuracy: 0.5072 - F1: 0.4477
sub_5:Test (Best Model) - Loss: 2.0345 - Accuracy: 0.4706 - F1: 0.3843
sub_20:Test (Best Model) - Loss: 1.9104 - Accuracy: 0.6912 - F1: 0.6161
sub_3:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.7826 - F1: 0.7784
sub_6:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.6812 - F1: 0.6260
sub_28:Test (Best Model) - Loss: 2.3444 - Accuracy: 0.4559 - F1: 0.3657
sub_25:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.7794 - F1: 0.7864
sub_26:Test (Best Model) - Loss: 1.2421 - Accuracy: 0.6471 - F1: 0.6467
sub_29:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.7647 - F1: 0.7231
sub_12:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.7681 - F1: 0.7681
sub_27:Test (Best Model) - Loss: 1.4461 - Accuracy: 0.6232 - F1: 0.6390
sub_22:Test (Best Model) - Loss: 1.1029 - Accuracy: 0.6765 - F1: 0.6313
sub_16:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.6765 - F1: 0.6679
sub_17:Test (Best Model) - Loss: 1.4461 - Accuracy: 0.6232 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 2.0956 - Accuracy: 0.5147 - F1: 0.4715
sub_18:Test (Best Model) - Loss: 2.7311 - Accuracy: 0.5147 - F1: 0.4703
sub_10:Test (Best Model) - Loss: 1.2403 - Accuracy: 0.6522 - F1: 0.6151
sub_14:Test (Best Model) - Loss: 1.1696 - Accuracy: 0.6471 - F1: 0.6080
sub_2:Test (Best Model) - Loss: 1.1072 - Accuracy: 0.7500 - F1: 0.7215
sub_1:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.7536 - F1: 0.7633
sub_6:Test (Best Model) - Loss: 1.0453 - Accuracy: 0.6957 - F1: 0.6376
sub_28:Test (Best Model) - Loss: 2.9338 - Accuracy: 0.3529 - F1: 0.2600
sub_4:Test (Best Model) - Loss: 1.7855 - Accuracy: 0.7246 - F1: 0.6523
sub_26:Test (Best Model) - Loss: 1.1983 - Accuracy: 0.5441 - F1: 0.5254
sub_8:Test (Best Model) - Loss: 2.2523 - Accuracy: 0.6471 - F1: 0.6205
sub_24:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.7794 - F1: 0.7929
sub_15:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.7500 - F1: 0.7419
sub_19:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.7059 - F1: 0.7128
sub_11:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7391 - F1: 0.7390
sub_3:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.5362 - F1: 0.4801
sub_25:Test (Best Model) - Loss: 1.4900 - Accuracy: 0.6912 - F1: 0.6757
sub_27:Test (Best Model) - Loss: 1.8186 - Accuracy: 0.4928 - F1: 0.4646
sub_16:Test (Best Model) - Loss: 1.3059 - Accuracy: 0.5294 - F1: 0.4993
sub_7:Test (Best Model) - Loss: 1.2263 - Accuracy: 0.6618 - F1: 0.5874
sub_21:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.8235 - F1: 0.8155
sub_5:Test (Best Model) - Loss: 2.2253 - Accuracy: 0.6471 - F1: 0.5757
sub_12:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.7681 - F1: 0.7720
sub_13:Test (Best Model) - Loss: 1.8229 - Accuracy: 0.4493 - F1: 0.3947
sub_17:Test (Best Model) - Loss: 1.8186 - Accuracy: 0.4928 - F1: 0.4646
sub_20:Test (Best Model) - Loss: 0.8633 - Accuracy: 0.7059 - F1: 0.6419
sub_14:Test (Best Model) - Loss: 0.7362 - Accuracy: 0.7500 - F1: 0.7073
sub_22:Test (Best Model) - Loss: 1.7602 - Accuracy: 0.5588 - F1: 0.5804
sub_28:Test (Best Model) - Loss: 2.9784 - Accuracy: 0.4706 - F1: 0.3188
sub_2:Test (Best Model) - Loss: 0.8928 - Accuracy: 0.6812 - F1: 0.6700
sub_18:Test (Best Model) - Loss: 1.5346 - Accuracy: 0.5735 - F1: 0.5759
sub_9:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.5735 - F1: 0.5081
sub_23:Test (Best Model) - Loss: 2.7358 - Accuracy: 0.4559 - F1: 0.3663
sub_10:Test (Best Model) - Loss: 1.5195 - Accuracy: 0.6812 - F1: 0.6089
sub_24:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.8235 - F1: 0.8298
sub_16:Test (Best Model) - Loss: 0.5938 - Accuracy: 0.8235 - F1: 0.8162
sub_3:Test (Best Model) - Loss: 0.9927 - Accuracy: 0.6667 - F1: 0.6277
sub_4:Test (Best Model) - Loss: 1.8307 - Accuracy: 0.7391 - F1: 0.6667
sub_29:Test (Best Model) - Loss: 0.1411 - Accuracy: 0.9265 - F1: 0.9300
sub_5:Test (Best Model) - Loss: 1.2717 - Accuracy: 0.7206 - F1: 0.6393
sub_8:Test (Best Model) - Loss: 1.5679 - Accuracy: 0.7059 - F1: 0.6813
sub_6:Test (Best Model) - Loss: 2.0824 - Accuracy: 0.7101 - F1: 0.6363
sub_25:Test (Best Model) - Loss: 1.5085 - Accuracy: 0.6912 - F1: 0.6643
sub_21:Test (Best Model) - Loss: 0.0567 - Accuracy: 0.9853 - F1: 0.9840
sub_11:Test (Best Model) - Loss: 0.9329 - Accuracy: 0.7536 - F1: 0.7193
sub_2:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.6522 - F1: 0.6036
sub_7:Test (Best Model) - Loss: 1.0667 - Accuracy: 0.7206 - F1: 0.6956
sub_13:Test (Best Model) - Loss: 1.5027 - Accuracy: 0.4493 - F1: 0.4488
sub_18:Test (Best Model) - Loss: 1.7247 - Accuracy: 0.5147 - F1: 0.4886
sub_1:Test (Best Model) - Loss: 1.2674 - Accuracy: 0.7246 - F1: 0.7024
sub_10:Test (Best Model) - Loss: 0.9935 - Accuracy: 0.6667 - F1: 0.6242
sub_26:Test (Best Model) - Loss: 2.1437 - Accuracy: 0.5588 - F1: 0.5360
sub_23:Test (Best Model) - Loss: 2.9859 - Accuracy: 0.5072 - F1: 0.4546
sub_15:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.8235 - F1: 0.8181
sub_14:Test (Best Model) - Loss: 0.3213 - Accuracy: 0.8971 - F1: 0.8985
sub_12:Test (Best Model) - Loss: 0.9912 - Accuracy: 0.7500 - F1: 0.7540
sub_16:Test (Best Model) - Loss: 0.4330 - Accuracy: 0.8382 - F1: 0.8332
sub_27:Test (Best Model) - Loss: 2.5878 - Accuracy: 0.6176 - F1: 0.5839
sub_9:Test (Best Model) - Loss: 1.4676 - Accuracy: 0.6471 - F1: 0.6408
sub_28:Test (Best Model) - Loss: 3.0667 - Accuracy: 0.5147 - F1: 0.4004
sub_22:Test (Best Model) - Loss: 1.1759 - Accuracy: 0.6618 - F1: 0.6824
sub_17:Test (Best Model) - Loss: 2.5878 - Accuracy: 0.6176 - F1: 0.5839
sub_20:Test (Best Model) - Loss: 2.8501 - Accuracy: 0.6377 - F1: 0.5885
sub_3:Test (Best Model) - Loss: 1.5428 - Accuracy: 0.6232 - F1: 0.5917
sub_29:Test (Best Model) - Loss: 1.6452 - Accuracy: 0.6957 - F1: 0.6319
sub_25:Test (Best Model) - Loss: 1.1815 - Accuracy: 0.7206 - F1: 0.6925
sub_8:Test (Best Model) - Loss: 2.3258 - Accuracy: 0.6471 - F1: 0.6025
sub_6:Test (Best Model) - Loss: 1.6527 - Accuracy: 0.6957 - F1: 0.6205
sub_21:Test (Best Model) - Loss: 0.4667 - Accuracy: 0.8529 - F1: 0.8495
sub_18:Test (Best Model) - Loss: 1.0026 - Accuracy: 0.6471 - F1: 0.6118
sub_5:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.7353 - F1: 0.6518
sub_11:Test (Best Model) - Loss: 0.3243 - Accuracy: 0.8986 - F1: 0.9021
sub_23:Test (Best Model) - Loss: 2.5431 - Accuracy: 0.5652 - F1: 0.5145
sub_10:Test (Best Model) - Loss: 1.2585 - Accuracy: 0.6522 - F1: 0.5762
sub_2:Test (Best Model) - Loss: 1.3003 - Accuracy: 0.7246 - F1: 0.6513
sub_24:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.7500 - F1: 0.7373
sub_19:Test (Best Model) - Loss: 3.1074 - Accuracy: 0.4412 - F1: 0.3206
sub_16:Test (Best Model) - Loss: 0.5231 - Accuracy: 0.8529 - F1: 0.8525
sub_20:Test (Best Model) - Loss: 0.5637 - Accuracy: 0.7826 - F1: 0.7883
sub_4:Test (Best Model) - Loss: 1.5020 - Accuracy: 0.7391 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 3.3344 - Accuracy: 0.4265 - F1: 0.3514
sub_7:Test (Best Model) - Loss: 0.4846 - Accuracy: 0.8088 - F1: 0.8002
sub_12:Test (Best Model) - Loss: 1.4126 - Accuracy: 0.6029 - F1: 0.5768
sub_14:Test (Best Model) - Loss: 1.1782 - Accuracy: 0.7353 - F1: 0.6804
sub_28:Test (Best Model) - Loss: 3.1758 - Accuracy: 0.2647 - F1: 0.2064
sub_15:Test (Best Model) - Loss: 0.4498 - Accuracy: 0.8235 - F1: 0.8274
sub_22:Test (Best Model) - Loss: 2.7363 - Accuracy: 0.4559 - F1: 0.4746
sub_3:Test (Best Model) - Loss: 1.2993 - Accuracy: 0.6232 - F1: 0.5909
sub_27:Test (Best Model) - Loss: 1.2847 - Accuracy: 0.6912 - F1: 0.6799
sub_18:Test (Best Model) - Loss: 1.8285 - Accuracy: 0.5147 - F1: 0.4731
sub_6:Test (Best Model) - Loss: 1.5061 - Accuracy: 0.7246 - F1: 0.6678
sub_9:Test (Best Model) - Loss: 4.0124 - Accuracy: 0.5000 - F1: 0.4286
sub_17:Test (Best Model) - Loss: 1.2847 - Accuracy: 0.6912 - F1: 0.6799
sub_26:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.7353 - F1: 0.7435
sub_1:Test (Best Model) - Loss: 2.2048 - Accuracy: 0.7206 - F1: 0.6509
sub_29:Test (Best Model) - Loss: 1.8338 - Accuracy: 0.6957 - F1: 0.6398
sub_8:Test (Best Model) - Loss: 2.6138 - Accuracy: 0.6176 - F1: 0.5804
sub_21:Test (Best Model) - Loss: 1.0337 - Accuracy: 0.7647 - F1: 0.7352
sub_24:Test (Best Model) - Loss: 0.4944 - Accuracy: 0.7941 - F1: 0.8061
sub_12:Test (Best Model) - Loss: 1.7028 - Accuracy: 0.6029 - F1: 0.5475
sub_2:Test (Best Model) - Loss: 2.7306 - Accuracy: 0.4783 - F1: 0.3577
sub_5:Test (Best Model) - Loss: 2.7613 - Accuracy: 0.5735 - F1: 0.5144
sub_23:Test (Best Model) - Loss: 3.3528 - Accuracy: 0.5072 - F1: 0.4531
sub_28:Test (Best Model) - Loss: 3.0475 - Accuracy: 0.4559 - F1: 0.3124
sub_20:Test (Best Model) - Loss: 1.2641 - Accuracy: 0.7246 - F1: 0.7193
sub_11:Test (Best Model) - Loss: 0.9153 - Accuracy: 0.7391 - F1: 0.7286
sub_4:Test (Best Model) - Loss: 2.4366 - Accuracy: 0.6957 - F1: 0.6457
sub_19:Test (Best Model) - Loss: 3.1379 - Accuracy: 0.4412 - F1: 0.3679
sub_13:Test (Best Model) - Loss: 3.9585 - Accuracy: 0.4559 - F1: 0.3182
sub_6:Test (Best Model) - Loss: 1.7695 - Accuracy: 0.6667 - F1: 0.5898
sub_24:Test (Best Model) - Loss: 0.4397 - Accuracy: 0.8088 - F1: 0.8177
sub_26:Test (Best Model) - Loss: 0.8159 - Accuracy: 0.8088 - F1: 0.8099
sub_15:Test (Best Model) - Loss: 3.4329 - Accuracy: 0.6176 - F1: 0.5422
sub_2:Test (Best Model) - Loss: 2.1115 - Accuracy: 0.6812 - F1: 0.6325
sub_12:Test (Best Model) - Loss: 0.4958 - Accuracy: 0.8382 - F1: 0.8397
sub_7:Test (Best Model) - Loss: 0.7912 - Accuracy: 0.7794 - F1: 0.7713
sub_20:Test (Best Model) - Loss: 1.8946 - Accuracy: 0.6522 - F1: 0.6216
sub_27:Test (Best Model) - Loss: 2.4110 - Accuracy: 0.6029 - F1: 0.5422
sub_9:Test (Best Model) - Loss: 2.1256 - Accuracy: 0.6176 - F1: 0.5702
sub_17:Test (Best Model) - Loss: 2.4110 - Accuracy: 0.6029 - F1: 0.5422
sub_1:Test (Best Model) - Loss: 2.1093 - Accuracy: 0.6912 - F1: 0.6527
sub_23:Test (Best Model) - Loss: 2.8227 - Accuracy: 0.5507 - F1: 0.5022
sub_20:Test (Best Model) - Loss: 1.0713 - Accuracy: 0.6957 - F1: 0.6719
sub_29:Test (Best Model) - Loss: 1.9806 - Accuracy: 0.6232 - F1: 0.5927
sub_12:Test (Best Model) - Loss: 0.8527 - Accuracy: 0.7206 - F1: 0.7034
sub_19:Test (Best Model) - Loss: 2.2590 - Accuracy: 0.5294 - F1: 0.4714
sub_21:Test (Best Model) - Loss: 0.0297 - Accuracy: 0.9853 - F1: 0.9840
sub_13:Test (Best Model) - Loss: 3.4006 - Accuracy: 0.4853 - F1: 0.3845
sub_9:Test (Best Model) - Loss: 1.0981 - Accuracy: 0.6618 - F1: 0.6529
sub_23:Test (Best Model) - Loss: 2.2437 - Accuracy: 0.4493 - F1: 0.3818
sub_27:Test (Best Model) - Loss: 1.1067 - Accuracy: 0.7059 - F1: 0.6605
sub_15:Test (Best Model) - Loss: 3.6961 - Accuracy: 0.5000 - F1: 0.3774
sub_1:Test (Best Model) - Loss: 1.9532 - Accuracy: 0.7353 - F1: 0.6804
sub_17:Test (Best Model) - Loss: 1.1067 - Accuracy: 0.7059 - F1: 0.6605
sub_29:Test (Best Model) - Loss: 1.0853 - Accuracy: 0.6812 - F1: 0.6328
sub_21:Test (Best Model) - Loss: 0.1293 - Accuracy: 0.9706 - F1: 0.9721
sub_19:Test (Best Model) - Loss: 3.0981 - Accuracy: 0.4412 - F1: 0.3615
sub_13:Test (Best Model) - Loss: 2.9850 - Accuracy: 0.5147 - F1: 0.4082
sub_27:Test (Best Model) - Loss: 2.5026 - Accuracy: 0.6618 - F1: 0.6131
sub_17:Test (Best Model) - Loss: 2.5026 - Accuracy: 0.6618 - F1: 0.6131
sub_1:Test (Best Model) - Loss: 1.4237 - Accuracy: 0.7353 - F1: 0.6842
sub_15:Test (Best Model) - Loss: 1.7408 - Accuracy: 0.6324 - F1: 0.5591
sub_19:Test (Best Model) - Loss: 1.7089 - Accuracy: 0.4559 - F1: 0.3984
sub_29:Test (Best Model) - Loss: 1.9658 - Accuracy: 0.7101 - F1: 0.6407
sub_1:Test (Best Model) - Loss: 2.3228 - Accuracy: 0.6912 - F1: 0.6353
sub_15:Test (Best Model) - Loss: 2.6928 - Accuracy: 0.5588 - F1: 0.4775
sub_13:Test (Best Model) - Loss: 2.0930 - Accuracy: 0.5882 - F1: 0.5450
sub_15:Test (Best Model) - Loss: 2.8690 - Accuracy: 0.5588 - F1: 0.4699

=== Summary Results ===

acc: 65.40 ± 9.37
F1: 61.85 ± 10.67
acc-in: 97.54 ± 1.46
F1-in: 97.45 ± 1.53
