lr: 1e-05
sub_10:Test (Best Model) - Loss: 1.0682 - Accuracy: 0.4265 - F1: 0.4245
sub_23:Test (Best Model) - Loss: 0.9821 - Accuracy: 0.5072 - F1: 0.4552
sub_27:Test (Best Model) - Loss: 0.9448 - Accuracy: 0.5797 - F1: 0.5633
sub_11:Test (Best Model) - Loss: 1.0121 - Accuracy: 0.5217 - F1: 0.5087
sub_15:Test (Best Model) - Loss: 0.9352 - Accuracy: 0.5441 - F1: 0.5073
sub_17:Test (Best Model) - Loss: 0.9448 - Accuracy: 0.5797 - F1: 0.5633
sub_5:Test (Best Model) - Loss: 1.0150 - Accuracy: 0.5735 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 1.3289 - Accuracy: 0.5441 - F1: 0.5087
sub_20:Test (Best Model) - Loss: 0.8741 - Accuracy: 0.7059 - F1: 0.6884
sub_12:Test (Best Model) - Loss: 1.1734 - Accuracy: 0.4559 - F1: 0.3803
sub_13:Test (Best Model) - Loss: 0.9961 - Accuracy: 0.5882 - F1: 0.5393
sub_25:Test (Best Model) - Loss: 0.3802 - Accuracy: 0.9130 - F1: 0.9125
sub_16:Test (Best Model) - Loss: 0.9805 - Accuracy: 0.6176 - F1: 0.6266
sub_28:Test (Best Model) - Loss: 1.0935 - Accuracy: 0.3971 - F1: 0.3465
sub_1:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.6471 - F1: 0.6739
sub_24:Test (Best Model) - Loss: 0.9266 - Accuracy: 0.5588 - F1: 0.5143
sub_4:Test (Best Model) - Loss: 1.0279 - Accuracy: 0.5072 - F1: 0.4286
sub_14:Test (Best Model) - Loss: 1.2466 - Accuracy: 0.3971 - F1: 0.3684
sub_3:Test (Best Model) - Loss: 0.7730 - Accuracy: 0.8088 - F1: 0.8126
sub_7:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8529 - F1: 0.8521
sub_29:Test (Best Model) - Loss: 0.9125 - Accuracy: 0.4559 - F1: 0.4743
sub_22:Test (Best Model) - Loss: 1.1589 - Accuracy: 0.3676 - F1: 0.3573
sub_26:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.7101 - F1: 0.6884
sub_19:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.3971 - F1: 0.3611
sub_9:Test (Best Model) - Loss: 0.7396 - Accuracy: 0.7353 - F1: 0.7427
sub_6:Test (Best Model) - Loss: 0.9586 - Accuracy: 0.5735 - F1: 0.5181
sub_21:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.8529 - F1: 0.8471
sub_11:Test (Best Model) - Loss: 1.0401 - Accuracy: 0.5797 - F1: 0.5260
sub_23:Test (Best Model) - Loss: 0.9318 - Accuracy: 0.6957 - F1: 0.6440
sub_2:Test (Best Model) - Loss: 0.8644 - Accuracy: 0.5942 - F1: 0.5838
sub_18:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.6667 - F1: 0.6841
sub_27:Test (Best Model) - Loss: 0.9168 - Accuracy: 0.6232 - F1: 0.5628
sub_17:Test (Best Model) - Loss: 0.9168 - Accuracy: 0.6232 - F1: 0.5628
sub_10:Test (Best Model) - Loss: 1.1306 - Accuracy: 0.4853 - F1: 0.4751
sub_8:Test (Best Model) - Loss: 0.8670 - Accuracy: 0.6912 - F1: 0.6469
sub_25:Test (Best Model) - Loss: 0.5892 - Accuracy: 0.9275 - F1: 0.9305
sub_20:Test (Best Model) - Loss: 0.9633 - Accuracy: 0.5735 - F1: 0.5403
sub_16:Test (Best Model) - Loss: 1.0508 - Accuracy: 0.5588 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.8655 - Accuracy: 0.6324 - F1: 0.6321
sub_28:Test (Best Model) - Loss: 1.2080 - Accuracy: 0.4265 - F1: 0.3956
sub_5:Test (Best Model) - Loss: 0.9537 - Accuracy: 0.6324 - F1: 0.5872
sub_3:Test (Best Model) - Loss: 0.7901 - Accuracy: 0.7353 - F1: 0.7280
sub_12:Test (Best Model) - Loss: 0.9699 - Accuracy: 0.6471 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.8270 - Accuracy: 0.6324 - F1: 0.6492
sub_6:Test (Best Model) - Loss: 0.9332 - Accuracy: 0.6765 - F1: 0.6816
sub_21:Test (Best Model) - Loss: 0.9431 - Accuracy: 0.6471 - F1: 0.6551
sub_14:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.4265 - F1: 0.3675
sub_7:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.8971 - F1: 0.8901
sub_13:Test (Best Model) - Loss: 1.0471 - Accuracy: 0.5735 - F1: 0.5242
sub_19:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.4265 - F1: 0.3925
sub_26:Test (Best Model) - Loss: 0.8349 - Accuracy: 0.5652 - F1: 0.5779
sub_11:Test (Best Model) - Loss: 0.9541 - Accuracy: 0.5652 - F1: 0.5633
sub_2:Test (Best Model) - Loss: 0.9369 - Accuracy: 0.6377 - F1: 0.5762
sub_9:Test (Best Model) - Loss: 1.0393 - Accuracy: 0.6029 - F1: 0.5975
sub_4:Test (Best Model) - Loss: 0.9977 - Accuracy: 0.6232 - F1: 0.5754
sub_24:Test (Best Model) - Loss: 0.9734 - Accuracy: 0.5882 - F1: 0.5687
sub_29:Test (Best Model) - Loss: 0.8444 - Accuracy: 0.5588 - F1: 0.5719
sub_8:Test (Best Model) - Loss: 1.0723 - Accuracy: 0.4412 - F1: 0.4339
sub_18:Test (Best Model) - Loss: 0.8145 - Accuracy: 0.6667 - F1: 0.6788
sub_22:Test (Best Model) - Loss: 0.8996 - Accuracy: 0.6176 - F1: 0.5960
sub_10:Test (Best Model) - Loss: 1.2100 - Accuracy: 0.4559 - F1: 0.4532
sub_23:Test (Best Model) - Loss: 0.7672 - Accuracy: 0.6522 - F1: 0.6570
sub_6:Test (Best Model) - Loss: 1.2998 - Accuracy: 0.4265 - F1: 0.3517
sub_20:Test (Best Model) - Loss: 0.9794 - Accuracy: 0.5588 - F1: 0.5301
sub_15:Test (Best Model) - Loss: 0.7670 - Accuracy: 0.7059 - F1: 0.7244
sub_27:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.7101 - F1: 0.7088
sub_17:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.7101 - F1: 0.7088
sub_5:Test (Best Model) - Loss: 1.1551 - Accuracy: 0.6912 - F1: 0.6258
sub_25:Test (Best Model) - Loss: 0.4059 - Accuracy: 0.8986 - F1: 0.8996
sub_19:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.4412 - F1: 0.4405
sub_26:Test (Best Model) - Loss: 0.7656 - Accuracy: 0.6377 - F1: 0.6381
sub_3:Test (Best Model) - Loss: 0.8860 - Accuracy: 0.5588 - F1: 0.5333
sub_11:Test (Best Model) - Loss: 1.0481 - Accuracy: 0.4928 - F1: 0.4798
sub_16:Test (Best Model) - Loss: 1.0005 - Accuracy: 0.5735 - F1: 0.5689
sub_28:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.3824 - F1: 0.2907
sub_13:Test (Best Model) - Loss: 1.3341 - Accuracy: 0.3235 - F1: 0.2870
sub_12:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.7647 - F1: 0.7683
sub_21:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.7941 - F1: 0.8002
sub_14:Test (Best Model) - Loss: 1.6417 - Accuracy: 0.4265 - F1: 0.3332
sub_2:Test (Best Model) - Loss: 0.9888 - Accuracy: 0.5507 - F1: 0.5538
sub_4:Test (Best Model) - Loss: 0.9246 - Accuracy: 0.6087 - F1: 0.5890
sub_24:Test (Best Model) - Loss: 1.0584 - Accuracy: 0.5147 - F1: 0.4633
sub_8:Test (Best Model) - Loss: 1.0073 - Accuracy: 0.6912 - F1: 0.6200
sub_7:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.6912 - F1: 0.6740
sub_9:Test (Best Model) - Loss: 0.8008 - Accuracy: 0.6765 - F1: 0.6789
sub_1:Test (Best Model) - Loss: 0.8224 - Accuracy: 0.7500 - F1: 0.7546
sub_20:Test (Best Model) - Loss: 0.8715 - Accuracy: 0.7206 - F1: 0.7015
sub_29:Test (Best Model) - Loss: 0.9536 - Accuracy: 0.5147 - F1: 0.5159
sub_22:Test (Best Model) - Loss: 0.9998 - Accuracy: 0.5294 - F1: 0.4756
sub_18:Test (Best Model) - Loss: 0.8746 - Accuracy: 0.6957 - F1: 0.6540
sub_5:Test (Best Model) - Loss: 1.1300 - Accuracy: 0.5441 - F1: 0.5191
sub_15:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.8382 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 1.0179 - Accuracy: 0.5735 - F1: 0.5501
sub_23:Test (Best Model) - Loss: 1.0666 - Accuracy: 0.5507 - F1: 0.5634
sub_27:Test (Best Model) - Loss: 0.5124 - Accuracy: 0.9130 - F1: 0.9162
sub_13:Test (Best Model) - Loss: 1.1749 - Accuracy: 0.5294 - F1: 0.5232
sub_17:Test (Best Model) - Loss: 0.5124 - Accuracy: 0.9130 - F1: 0.9162
sub_11:Test (Best Model) - Loss: 1.1559 - Accuracy: 0.5942 - F1: 0.5455
sub_10:Test (Best Model) - Loss: 0.7588 - Accuracy: 0.7500 - F1: 0.7628
sub_25:Test (Best Model) - Loss: 0.4047 - Accuracy: 0.8551 - F1: 0.8545
sub_3:Test (Best Model) - Loss: 0.8209 - Accuracy: 0.6471 - F1: 0.6203
sub_19:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.4559 - F1: 0.3697
sub_16:Test (Best Model) - Loss: 0.8365 - Accuracy: 0.6618 - F1: 0.6627
sub_2:Test (Best Model) - Loss: 1.0024 - Accuracy: 0.5942 - F1: 0.5590
sub_28:Test (Best Model) - Loss: 0.9861 - Accuracy: 0.4853 - F1: 0.4806
sub_12:Test (Best Model) - Loss: 0.7797 - Accuracy: 0.6765 - F1: 0.6862
sub_1:Test (Best Model) - Loss: 0.8872 - Accuracy: 0.6176 - F1: 0.5905
sub_9:Test (Best Model) - Loss: 0.8907 - Accuracy: 0.5735 - F1: 0.5693
sub_26:Test (Best Model) - Loss: 0.7994 - Accuracy: 0.7101 - F1: 0.7243
sub_20:Test (Best Model) - Loss: 0.9791 - Accuracy: 0.6176 - F1: 0.6029
sub_21:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.7500 - F1: 0.7557
sub_14:Test (Best Model) - Loss: 1.8106 - Accuracy: 0.4118 - F1: 0.3300
sub_4:Test (Best Model) - Loss: 0.7474 - Accuracy: 0.6377 - F1: 0.6378
sub_8:Test (Best Model) - Loss: 1.0554 - Accuracy: 0.6176 - F1: 0.5653
sub_23:Test (Best Model) - Loss: 1.0749 - Accuracy: 0.4928 - F1: 0.4872
sub_7:Test (Best Model) - Loss: 0.8646 - Accuracy: 0.6471 - F1: 0.6511
sub_24:Test (Best Model) - Loss: 1.0301 - Accuracy: 0.6029 - F1: 0.6017
sub_5:Test (Best Model) - Loss: 0.9274 - Accuracy: 0.6912 - F1: 0.6204
sub_6:Test (Best Model) - Loss: 1.0336 - Accuracy: 0.6176 - F1: 0.6135
sub_16:Test (Best Model) - Loss: 1.1550 - Accuracy: 0.4559 - F1: 0.4896
sub_22:Test (Best Model) - Loss: 0.9890 - Accuracy: 0.4853 - F1: 0.4670
sub_13:Test (Best Model) - Loss: 1.1210 - Accuracy: 0.5441 - F1: 0.5245
sub_11:Test (Best Model) - Loss: 0.8451 - Accuracy: 0.7246 - F1: 0.6910
sub_9:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.5294 - F1: 0.4948
sub_27:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.8116 - F1: 0.8157
sub_29:Test (Best Model) - Loss: 0.9397 - Accuracy: 0.5882 - F1: 0.6094
sub_3:Test (Best Model) - Loss: 1.1024 - Accuracy: 0.5294 - F1: 0.4915
sub_17:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.8116 - F1: 0.8157
sub_18:Test (Best Model) - Loss: 0.7883 - Accuracy: 0.6232 - F1: 0.6236
sub_19:Test (Best Model) - Loss: 1.7130 - Accuracy: 0.3676 - F1: 0.3321
sub_25:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.8551 - F1: 0.8576
sub_15:Test (Best Model) - Loss: 0.7519 - Accuracy: 0.7206 - F1: 0.7369
sub_10:Test (Best Model) - Loss: 1.1746 - Accuracy: 0.3971 - F1: 0.3543
sub_28:Test (Best Model) - Loss: 1.2721 - Accuracy: 0.4412 - F1: 0.3363
sub_2:Test (Best Model) - Loss: 0.9079 - Accuracy: 0.6522 - F1: 0.6534
sub_21:Test (Best Model) - Loss: 0.8289 - Accuracy: 0.7059 - F1: 0.6910
sub_20:Test (Best Model) - Loss: 1.0763 - Accuracy: 0.6324 - F1: 0.5807
sub_14:Test (Best Model) - Loss: 1.1461 - Accuracy: 0.5735 - F1: 0.5084
sub_12:Test (Best Model) - Loss: 0.8987 - Accuracy: 0.6029 - F1: 0.5661
sub_26:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.6377 - F1: 0.6152
sub_1:Test (Best Model) - Loss: 0.9747 - Accuracy: 0.6176 - F1: 0.6087
sub_4:Test (Best Model) - Loss: 0.8696 - Accuracy: 0.6377 - F1: 0.6478
sub_23:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.4412 - F1: 0.3723
sub_16:Test (Best Model) - Loss: 1.1329 - Accuracy: 0.4853 - F1: 0.4603
sub_5:Test (Best Model) - Loss: 1.0269 - Accuracy: 0.5147 - F1: 0.5135
sub_8:Test (Best Model) - Loss: 0.8955 - Accuracy: 0.6618 - F1: 0.5823
sub_7:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.7941 - F1: 0.7841
sub_15:Test (Best Model) - Loss: 1.1181 - Accuracy: 0.5294 - F1: 0.5309
sub_27:Test (Best Model) - Loss: 0.9632 - Accuracy: 0.6087 - F1: 0.6002
sub_6:Test (Best Model) - Loss: 0.9053 - Accuracy: 0.5652 - F1: 0.5752
sub_19:Test (Best Model) - Loss: 1.0244 - Accuracy: 0.5882 - F1: 0.5667
sub_17:Test (Best Model) - Loss: 0.9632 - Accuracy: 0.6087 - F1: 0.6002
sub_22:Test (Best Model) - Loss: 1.0269 - Accuracy: 0.4706 - F1: 0.4362
sub_9:Test (Best Model) - Loss: 0.8734 - Accuracy: 0.5147 - F1: 0.4351
sub_3:Test (Best Model) - Loss: 1.0095 - Accuracy: 0.5507 - F1: 0.5131
sub_11:Test (Best Model) - Loss: 0.8831 - Accuracy: 0.7101 - F1: 0.6932
sub_25:Test (Best Model) - Loss: 0.8832 - Accuracy: 0.6618 - F1: 0.6233
sub_24:Test (Best Model) - Loss: 0.8530 - Accuracy: 0.5882 - F1: 0.5682
sub_12:Test (Best Model) - Loss: 1.2276 - Accuracy: 0.4203 - F1: 0.3889
sub_10:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.3971 - F1: 0.3189
sub_13:Test (Best Model) - Loss: 0.9779 - Accuracy: 0.5652 - F1: 0.5580
sub_29:Test (Best Model) - Loss: 1.0304 - Accuracy: 0.5147 - F1: 0.5268
sub_18:Test (Best Model) - Loss: 0.8310 - Accuracy: 0.6377 - F1: 0.6515
sub_14:Test (Best Model) - Loss: 0.9882 - Accuracy: 0.5735 - F1: 0.5989
sub_2:Test (Best Model) - Loss: 0.7834 - Accuracy: 0.6618 - F1: 0.6372
sub_21:Test (Best Model) - Loss: 0.6394 - Accuracy: 0.7500 - F1: 0.7264
sub_23:Test (Best Model) - Loss: 1.1829 - Accuracy: 0.3824 - F1: 0.3580
sub_5:Test (Best Model) - Loss: 0.9406 - Accuracy: 0.6912 - F1: 0.7144
sub_28:Test (Best Model) - Loss: 1.7971 - Accuracy: 0.4118 - F1: 0.3333
sub_26:Test (Best Model) - Loss: 0.9328 - Accuracy: 0.5147 - F1: 0.4743
sub_20:Test (Best Model) - Loss: 0.7766 - Accuracy: 0.6618 - F1: 0.6223
sub_1:Test (Best Model) - Loss: 0.8610 - Accuracy: 0.5797 - F1: 0.5697
sub_27:Test (Best Model) - Loss: 1.0958 - Accuracy: 0.5507 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 1.0615 - Accuracy: 0.6618 - F1: 0.5834
sub_8:Test (Best Model) - Loss: 0.9788 - Accuracy: 0.6471 - F1: 0.5908
sub_6:Test (Best Model) - Loss: 0.9894 - Accuracy: 0.5797 - F1: 0.5515
sub_17:Test (Best Model) - Loss: 1.0958 - Accuracy: 0.5507 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 1.1093 - Accuracy: 0.5072 - F1: 0.5116
sub_9:Test (Best Model) - Loss: 0.9283 - Accuracy: 0.5294 - F1: 0.4707
sub_25:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.7206 - F1: 0.7191
sub_4:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.7101 - F1: 0.6687
sub_10:Test (Best Model) - Loss: 1.4194 - Accuracy: 0.2647 - F1: 0.1418
sub_15:Test (Best Model) - Loss: 1.0902 - Accuracy: 0.4706 - F1: 0.4051
sub_3:Test (Best Model) - Loss: 1.0530 - Accuracy: 0.6667 - F1: 0.5966
sub_16:Test (Best Model) - Loss: 0.9592 - Accuracy: 0.5882 - F1: 0.5896
sub_18:Test (Best Model) - Loss: 0.8717 - Accuracy: 0.5882 - F1: 0.5487
sub_13:Test (Best Model) - Loss: 0.9844 - Accuracy: 0.5507 - F1: 0.4818
sub_29:Test (Best Model) - Loss: 0.9104 - Accuracy: 0.5735 - F1: 0.5037
sub_5:Test (Best Model) - Loss: 1.1290 - Accuracy: 0.5147 - F1: 0.4834
sub_1:Test (Best Model) - Loss: 1.0807 - Accuracy: 0.5362 - F1: 0.5171
sub_14:Test (Best Model) - Loss: 0.9336 - Accuracy: 0.4853 - F1: 0.5005
sub_24:Test (Best Model) - Loss: 0.8399 - Accuracy: 0.6324 - F1: 0.5905
sub_19:Test (Best Model) - Loss: 0.9260 - Accuracy: 0.4853 - F1: 0.4301
sub_2:Test (Best Model) - Loss: 0.8827 - Accuracy: 0.5882 - F1: 0.5665
sub_21:Test (Best Model) - Loss: 0.8137 - Accuracy: 0.7794 - F1: 0.7785
sub_12:Test (Best Model) - Loss: 0.9248 - Accuracy: 0.5942 - F1: 0.5890
sub_11:Test (Best Model) - Loss: 0.8893 - Accuracy: 0.6667 - F1: 0.6255
sub_26:Test (Best Model) - Loss: 0.9916 - Accuracy: 0.6765 - F1: 0.6761
sub_22:Test (Best Model) - Loss: 1.2391 - Accuracy: 0.3913 - F1: 0.3570
sub_6:Test (Best Model) - Loss: 1.0123 - Accuracy: 0.5507 - F1: 0.5179
sub_7:Test (Best Model) - Loss: 1.0164 - Accuracy: 0.5735 - F1: 0.5752
sub_20:Test (Best Model) - Loss: 0.8597 - Accuracy: 0.6765 - F1: 0.6417
sub_8:Test (Best Model) - Loss: 1.0049 - Accuracy: 0.6618 - F1: 0.5892
sub_23:Test (Best Model) - Loss: 1.5146 - Accuracy: 0.3382 - F1: 0.2467
sub_27:Test (Best Model) - Loss: 0.9572 - Accuracy: 0.5072 - F1: 0.4859
sub_25:Test (Best Model) - Loss: 0.9703 - Accuracy: 0.6765 - F1: 0.6472
sub_15:Test (Best Model) - Loss: 1.0427 - Accuracy: 0.6029 - F1: 0.5707
sub_18:Test (Best Model) - Loss: 1.1142 - Accuracy: 0.5294 - F1: 0.4601
sub_17:Test (Best Model) - Loss: 0.9572 - Accuracy: 0.5072 - F1: 0.4859
sub_4:Test (Best Model) - Loss: 0.8453 - Accuracy: 0.7391 - F1: 0.7398
sub_10:Test (Best Model) - Loss: 1.4817 - Accuracy: 0.3382 - F1: 0.2804
sub_28:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.4412 - F1: 0.3558
sub_16:Test (Best Model) - Loss: 0.9716 - Accuracy: 0.5882 - F1: 0.5506
sub_9:Test (Best Model) - Loss: 0.7213 - Accuracy: 0.7353 - F1: 0.7329
sub_11:Test (Best Model) - Loss: 0.8565 - Accuracy: 0.6812 - F1: 0.6836
sub_20:Test (Best Model) - Loss: 0.8262 - Accuracy: 0.6471 - F1: 0.6088
sub_3:Test (Best Model) - Loss: 1.0294 - Accuracy: 0.5217 - F1: 0.4919
sub_2:Test (Best Model) - Loss: 0.8910 - Accuracy: 0.5882 - F1: 0.5658
sub_6:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.7971 - F1: 0.7943
sub_26:Test (Best Model) - Loss: 1.0298 - Accuracy: 0.4706 - F1: 0.4499
sub_14:Test (Best Model) - Loss: 1.0675 - Accuracy: 0.3529 - F1: 0.3280
sub_24:Test (Best Model) - Loss: 0.9973 - Accuracy: 0.6176 - F1: 0.5868
sub_5:Test (Best Model) - Loss: 0.7290 - Accuracy: 0.7500 - F1: 0.6973
sub_7:Test (Best Model) - Loss: 1.1269 - Accuracy: 0.6618 - F1: 0.6038
sub_1:Test (Best Model) - Loss: 0.9245 - Accuracy: 0.6087 - F1: 0.5873
sub_22:Test (Best Model) - Loss: 1.1709 - Accuracy: 0.5072 - F1: 0.4671
sub_29:Test (Best Model) - Loss: 0.9593 - Accuracy: 0.4559 - F1: 0.4205
sub_21:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7206 - F1: 0.6889
sub_12:Test (Best Model) - Loss: 1.0062 - Accuracy: 0.6377 - F1: 0.6335
sub_27:Test (Best Model) - Loss: 0.8841 - Accuracy: 0.5942 - F1: 0.5959
sub_8:Test (Best Model) - Loss: 0.9082 - Accuracy: 0.6765 - F1: 0.6272
sub_17:Test (Best Model) - Loss: 0.8841 - Accuracy: 0.5942 - F1: 0.5959
sub_4:Test (Best Model) - Loss: 0.8381 - Accuracy: 0.6522 - F1: 0.5895
sub_23:Test (Best Model) - Loss: 1.1571 - Accuracy: 0.4853 - F1: 0.4192
sub_19:Test (Best Model) - Loss: 0.9578 - Accuracy: 0.5000 - F1: 0.4862
sub_10:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.3088 - F1: 0.2142
sub_15:Test (Best Model) - Loss: 0.7360 - Accuracy: 0.7059 - F1: 0.7107
sub_13:Test (Best Model) - Loss: 0.9896 - Accuracy: 0.5507 - F1: 0.5373
sub_9:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.6471 - F1: 0.6100
sub_16:Test (Best Model) - Loss: 0.9876 - Accuracy: 0.4706 - F1: 0.5041
sub_18:Test (Best Model) - Loss: 1.0041 - Accuracy: 0.5441 - F1: 0.4953
sub_28:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.4559 - F1: 0.3657
sub_7:Test (Best Model) - Loss: 1.0201 - Accuracy: 0.6176 - F1: 0.5651
sub_6:Test (Best Model) - Loss: 0.9095 - Accuracy: 0.6087 - F1: 0.5689
sub_25:Test (Best Model) - Loss: 0.5346 - Accuracy: 0.7794 - F1: 0.7840
sub_14:Test (Best Model) - Loss: 1.0375 - Accuracy: 0.5441 - F1: 0.5330
sub_2:Test (Best Model) - Loss: 1.0063 - Accuracy: 0.5882 - F1: 0.5165
sub_21:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.8382 - F1: 0.8354
sub_1:Test (Best Model) - Loss: 0.9763 - Accuracy: 0.5072 - F1: 0.4702
sub_26:Test (Best Model) - Loss: 0.8906 - Accuracy: 0.6471 - F1: 0.5725
sub_20:Test (Best Model) - Loss: 0.8427 - Accuracy: 0.6765 - F1: 0.6363
sub_12:Test (Best Model) - Loss: 0.9292 - Accuracy: 0.5652 - F1: 0.5674
sub_22:Test (Best Model) - Loss: 0.9426 - Accuracy: 0.5942 - F1: 0.5891
sub_4:Test (Best Model) - Loss: 0.5838 - Accuracy: 0.7391 - F1: 0.6667
sub_24:Test (Best Model) - Loss: 0.8719 - Accuracy: 0.7206 - F1: 0.7161
sub_27:Test (Best Model) - Loss: 0.9681 - Accuracy: 0.5797 - F1: 0.5473
sub_8:Test (Best Model) - Loss: 0.9157 - Accuracy: 0.6618 - F1: 0.6033
sub_19:Test (Best Model) - Loss: 0.8602 - Accuracy: 0.6471 - F1: 0.6518
sub_11:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.7971 - F1: 0.7923
sub_29:Test (Best Model) - Loss: 0.9081 - Accuracy: 0.4706 - F1: 0.4778
sub_3:Test (Best Model) - Loss: 0.8557 - Accuracy: 0.5797 - F1: 0.5490
sub_28:Test (Best Model) - Loss: 1.8489 - Accuracy: 0.3382 - F1: 0.2500
sub_13:Test (Best Model) - Loss: 1.1000 - Accuracy: 0.5072 - F1: 0.4609
sub_17:Test (Best Model) - Loss: 0.9681 - Accuracy: 0.5797 - F1: 0.5473
sub_23:Test (Best Model) - Loss: 1.2280 - Accuracy: 0.3971 - F1: 0.2791
sub_9:Test (Best Model) - Loss: 0.8738 - Accuracy: 0.5735 - F1: 0.5329
sub_15:Test (Best Model) - Loss: 1.0748 - Accuracy: 0.5000 - F1: 0.5079
sub_5:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.7353 - F1: 0.6415
sub_7:Test (Best Model) - Loss: 1.0144 - Accuracy: 0.6176 - F1: 0.5657
sub_10:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.3676 - F1: 0.3245
sub_16:Test (Best Model) - Loss: 0.9764 - Accuracy: 0.5147 - F1: 0.4852
sub_2:Test (Best Model) - Loss: 1.0182 - Accuracy: 0.5588 - F1: 0.5565
sub_6:Test (Best Model) - Loss: 0.9286 - Accuracy: 0.6232 - F1: 0.5492
sub_25:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.7353 - F1: 0.6804
sub_4:Test (Best Model) - Loss: 0.9960 - Accuracy: 0.6667 - F1: 0.6643
sub_22:Test (Best Model) - Loss: 1.0196 - Accuracy: 0.5362 - F1: 0.5363
sub_24:Test (Best Model) - Loss: 1.0517 - Accuracy: 0.5441 - F1: 0.5031
sub_20:Test (Best Model) - Loss: 1.1348 - Accuracy: 0.5507 - F1: 0.5263
sub_18:Test (Best Model) - Loss: 0.8606 - Accuracy: 0.6029 - F1: 0.6046
sub_21:Test (Best Model) - Loss: 0.7475 - Accuracy: 0.6912 - F1: 0.6742
sub_1:Test (Best Model) - Loss: 0.8181 - Accuracy: 0.5942 - F1: 0.5928
sub_14:Test (Best Model) - Loss: 1.0758 - Accuracy: 0.4118 - F1: 0.4567
sub_23:Test (Best Model) - Loss: 1.0922 - Accuracy: 0.5072 - F1: 0.5198
sub_27:Test (Best Model) - Loss: 0.5668 - Accuracy: 0.7794 - F1: 0.7788
sub_8:Test (Best Model) - Loss: 0.9667 - Accuracy: 0.6618 - F1: 0.6037
sub_11:Test (Best Model) - Loss: 0.9824 - Accuracy: 0.6087 - F1: 0.5615
sub_19:Test (Best Model) - Loss: 0.8701 - Accuracy: 0.6176 - F1: 0.6098
sub_26:Test (Best Model) - Loss: 0.8983 - Accuracy: 0.6618 - F1: 0.6276
sub_5:Test (Best Model) - Loss: 0.9968 - Accuracy: 0.4853 - F1: 0.4243
sub_12:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.7391 - F1: 0.7454
sub_3:Test (Best Model) - Loss: 0.9857 - Accuracy: 0.5942 - F1: 0.5851
sub_28:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.4118 - F1: 0.3518
sub_9:Test (Best Model) - Loss: 0.8590 - Accuracy: 0.6176 - F1: 0.6094
sub_29:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.7059 - F1: 0.6432
sub_17:Test (Best Model) - Loss: 0.5668 - Accuracy: 0.7794 - F1: 0.7788
sub_13:Test (Best Model) - Loss: 0.8636 - Accuracy: 0.5797 - F1: 0.5643
sub_4:Test (Best Model) - Loss: 0.9685 - Accuracy: 0.5797 - F1: 0.5286
sub_7:Test (Best Model) - Loss: 0.8945 - Accuracy: 0.7353 - F1: 0.7430
sub_20:Test (Best Model) - Loss: 0.9383 - Accuracy: 0.5217 - F1: 0.5176
sub_10:Test (Best Model) - Loss: 0.8702 - Accuracy: 0.6667 - F1: 0.6082
sub_22:Test (Best Model) - Loss: 1.1142 - Accuracy: 0.5294 - F1: 0.5297
sub_6:Test (Best Model) - Loss: 0.8264 - Accuracy: 0.6957 - F1: 0.7018
sub_15:Test (Best Model) - Loss: 0.9605 - Accuracy: 0.5735 - F1: 0.5015
sub_25:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.7500 - F1: 0.7551
sub_16:Test (Best Model) - Loss: 1.0483 - Accuracy: 0.5441 - F1: 0.5163
sub_12:Test (Best Model) - Loss: 0.9732 - Accuracy: 0.5294 - F1: 0.5372
sub_2:Test (Best Model) - Loss: 0.8577 - Accuracy: 0.5072 - F1: 0.5231
sub_26:Test (Best Model) - Loss: 0.8261 - Accuracy: 0.6912 - F1: 0.7005
sub_23:Test (Best Model) - Loss: 1.3183 - Accuracy: 0.4638 - F1: 0.4162
sub_27:Test (Best Model) - Loss: 0.8649 - Accuracy: 0.6618 - F1: 0.6607
sub_1:Test (Best Model) - Loss: 1.0425 - Accuracy: 0.5882 - F1: 0.5119
sub_28:Test (Best Model) - Loss: 1.5761 - Accuracy: 0.2059 - F1: 0.1761
sub_18:Test (Best Model) - Loss: 0.7643 - Accuracy: 0.6912 - F1: 0.6904
sub_5:Test (Best Model) - Loss: 1.6777 - Accuracy: 0.4706 - F1: 0.3198
sub_21:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.7059 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 0.9176 - Accuracy: 0.6667 - F1: 0.6346
sub_8:Test (Best Model) - Loss: 1.1884 - Accuracy: 0.5441 - F1: 0.5490
sub_3:Test (Best Model) - Loss: 0.8527 - Accuracy: 0.6667 - F1: 0.6641
sub_17:Test (Best Model) - Loss: 0.8649 - Accuracy: 0.6618 - F1: 0.6607
sub_13:Test (Best Model) - Loss: 1.2742 - Accuracy: 0.3382 - F1: 0.2669
sub_14:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.7500 - F1: 0.7280
sub_19:Test (Best Model) - Loss: 1.1701 - Accuracy: 0.5588 - F1: 0.5082
sub_4:Test (Best Model) - Loss: 1.0017 - Accuracy: 0.5507 - F1: 0.5414
sub_24:Test (Best Model) - Loss: 0.8177 - Accuracy: 0.6618 - F1: 0.5933
sub_22:Test (Best Model) - Loss: 1.1101 - Accuracy: 0.5294 - F1: 0.5141
sub_9:Test (Best Model) - Loss: 1.2395 - Accuracy: 0.3971 - F1: 0.4199
sub_6:Test (Best Model) - Loss: 0.8938 - Accuracy: 0.6667 - F1: 0.6272
sub_25:Test (Best Model) - Loss: 0.8172 - Accuracy: 0.6176 - F1: 0.6416
sub_7:Test (Best Model) - Loss: 0.8646 - Accuracy: 0.6765 - F1: 0.6405
sub_26:Test (Best Model) - Loss: 0.9912 - Accuracy: 0.5294 - F1: 0.5606
sub_2:Test (Best Model) - Loss: 1.1191 - Accuracy: 0.4783 - F1: 0.4441
sub_1:Test (Best Model) - Loss: 1.0069 - Accuracy: 0.6029 - F1: 0.5838
sub_20:Test (Best Model) - Loss: 0.7986 - Accuracy: 0.6812 - F1: 0.6471
sub_15:Test (Best Model) - Loss: 1.1165 - Accuracy: 0.4706 - F1: 0.4244
sub_23:Test (Best Model) - Loss: 1.6247 - Accuracy: 0.3623 - F1: 0.3183
sub_29:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.7353 - F1: 0.7324
sub_16:Test (Best Model) - Loss: 1.1097 - Accuracy: 0.5147 - F1: 0.5241
sub_27:Test (Best Model) - Loss: 0.9739 - Accuracy: 0.5588 - F1: 0.5468
sub_10:Test (Best Model) - Loss: 1.0693 - Accuracy: 0.5652 - F1: 0.5199
sub_12:Test (Best Model) - Loss: 0.9030 - Accuracy: 0.6471 - F1: 0.5972
sub_18:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.4853 - F1: 0.4251
sub_3:Test (Best Model) - Loss: 0.7437 - Accuracy: 0.7826 - F1: 0.7902
sub_5:Test (Best Model) - Loss: 0.8472 - Accuracy: 0.6912 - F1: 0.6564
sub_11:Test (Best Model) - Loss: 0.9117 - Accuracy: 0.6667 - F1: 0.6389
sub_13:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.3382 - F1: 0.3059
sub_17:Test (Best Model) - Loss: 0.9739 - Accuracy: 0.5588 - F1: 0.5468
sub_21:Test (Best Model) - Loss: 1.0038 - Accuracy: 0.7206 - F1: 0.6609
sub_14:Test (Best Model) - Loss: 0.9674 - Accuracy: 0.5000 - F1: 0.5028
sub_25:Test (Best Model) - Loss: 1.0736 - Accuracy: 0.6618 - F1: 0.6154
sub_8:Test (Best Model) - Loss: 1.0746 - Accuracy: 0.6029 - F1: 0.5865
sub_28:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.3529 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.4412 - F1: 0.3786
sub_4:Test (Best Model) - Loss: 0.8616 - Accuracy: 0.6957 - F1: 0.6475
sub_2:Test (Best Model) - Loss: 0.9945 - Accuracy: 0.5652 - F1: 0.5324
sub_9:Test (Best Model) - Loss: 1.0768 - Accuracy: 0.5000 - F1: 0.4799
sub_7:Test (Best Model) - Loss: 1.2078 - Accuracy: 0.4853 - F1: 0.4883
sub_18:Test (Best Model) - Loss: 1.0681 - Accuracy: 0.4853 - F1: 0.4601
sub_24:Test (Best Model) - Loss: 1.0773 - Accuracy: 0.5147 - F1: 0.5152
sub_26:Test (Best Model) - Loss: 1.1456 - Accuracy: 0.4706 - F1: 0.4322
sub_6:Test (Best Model) - Loss: 0.8447 - Accuracy: 0.6087 - F1: 0.5441
sub_8:Test (Best Model) - Loss: 0.9562 - Accuracy: 0.6765 - F1: 0.6622
sub_20:Test (Best Model) - Loss: 0.7937 - Accuracy: 0.6377 - F1: 0.6274
sub_22:Test (Best Model) - Loss: 0.9752 - Accuracy: 0.5588 - F1: 0.5897
sub_16:Test (Best Model) - Loss: 0.9873 - Accuracy: 0.6176 - F1: 0.5939
sub_27:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.7353 - F1: 0.7442
sub_10:Test (Best Model) - Loss: 0.8213 - Accuracy: 0.6957 - F1: 0.6812
sub_1:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.7647 - F1: 0.7385
sub_15:Test (Best Model) - Loss: 1.1744 - Accuracy: 0.5000 - F1: 0.4347
sub_2:Test (Best Model) - Loss: 1.0034 - Accuracy: 0.5507 - F1: 0.5524
sub_29:Test (Best Model) - Loss: 0.7845 - Accuracy: 0.5797 - F1: 0.5013
sub_9:Test (Best Model) - Loss: 1.0590 - Accuracy: 0.5441 - F1: 0.5260
sub_25:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.7353 - F1: 0.7455
sub_23:Test (Best Model) - Loss: 1.1869 - Accuracy: 0.4783 - F1: 0.4547
sub_17:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.7353 - F1: 0.7442
sub_28:Test (Best Model) - Loss: 1.4095 - Accuracy: 0.2647 - F1: 0.2253
sub_5:Test (Best Model) - Loss: 0.9256 - Accuracy: 0.5588 - F1: 0.5079
sub_3:Test (Best Model) - Loss: 0.9976 - Accuracy: 0.6232 - F1: 0.5758
sub_11:Test (Best Model) - Loss: 0.8708 - Accuracy: 0.6232 - F1: 0.5999
sub_26:Test (Best Model) - Loss: 0.9680 - Accuracy: 0.6029 - F1: 0.6041
sub_14:Test (Best Model) - Loss: 0.8867 - Accuracy: 0.6029 - F1: 0.5922
sub_13:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.3382 - F1: 0.3062
sub_12:Test (Best Model) - Loss: 0.8822 - Accuracy: 0.6471 - F1: 0.6222
sub_21:Test (Best Model) - Loss: 1.0228 - Accuracy: 0.5294 - F1: 0.4449
sub_4:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.7101 - F1: 0.6460
sub_7:Test (Best Model) - Loss: 0.8245 - Accuracy: 0.6765 - F1: 0.6625
sub_19:Test (Best Model) - Loss: 0.9640 - Accuracy: 0.5882 - F1: 0.5760
sub_24:Test (Best Model) - Loss: 0.8616 - Accuracy: 0.6471 - F1: 0.6542
sub_29:Test (Best Model) - Loss: 1.3356 - Accuracy: 0.4783 - F1: 0.4089
sub_20:Test (Best Model) - Loss: 0.7391 - Accuracy: 0.7101 - F1: 0.7171
sub_22:Test (Best Model) - Loss: 1.0564 - Accuracy: 0.5294 - F1: 0.4949
sub_6:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.7681 - F1: 0.7700
sub_15:Test (Best Model) - Loss: 0.8474 - Accuracy: 0.6029 - F1: 0.5655
sub_23:Test (Best Model) - Loss: 1.2043 - Accuracy: 0.4203 - F1: 0.4125
sub_2:Test (Best Model) - Loss: 0.9779 - Accuracy: 0.5217 - F1: 0.4943
sub_8:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.7353 - F1: 0.7406
sub_9:Test (Best Model) - Loss: 1.1489 - Accuracy: 0.4265 - F1: 0.4423
sub_16:Test (Best Model) - Loss: 0.9073 - Accuracy: 0.6324 - F1: 0.6397
sub_18:Test (Best Model) - Loss: 1.1054 - Accuracy: 0.5441 - F1: 0.5333
sub_1:Test (Best Model) - Loss: 0.9038 - Accuracy: 0.6618 - F1: 0.6148
sub_26:Test (Best Model) - Loss: 1.0683 - Accuracy: 0.3824 - F1: 0.3791
sub_25:Test (Best Model) - Loss: 0.8505 - Accuracy: 0.5588 - F1: 0.5794
sub_5:Test (Best Model) - Loss: 1.0622 - Accuracy: 0.5441 - F1: 0.4996
sub_27:Test (Best Model) - Loss: 0.7810 - Accuracy: 0.6029 - F1: 0.6225
sub_7:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.7059 - F1: 0.7069
sub_28:Test (Best Model) - Loss: 1.2484 - Accuracy: 0.4559 - F1: 0.3713
sub_4:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6232 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6912 - F1: 0.6730
sub_10:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.7681 - F1: 0.7527
sub_21:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7353 - F1: 0.7104
sub_17:Test (Best Model) - Loss: 0.7810 - Accuracy: 0.6029 - F1: 0.6225
sub_19:Test (Best Model) - Loss: 0.9048 - Accuracy: 0.6618 - F1: 0.6687
sub_13:Test (Best Model) - Loss: 1.0925 - Accuracy: 0.4853 - F1: 0.4453
sub_11:Test (Best Model) - Loss: 0.7660 - Accuracy: 0.6232 - F1: 0.5990
sub_22:Test (Best Model) - Loss: 1.2052 - Accuracy: 0.3676 - F1: 0.3515
sub_3:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.6812 - F1: 0.6858
sub_12:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.7500 - F1: 0.7610
sub_15:Test (Best Model) - Loss: 1.0161 - Accuracy: 0.6029 - F1: 0.5300
sub_24:Test (Best Model) - Loss: 1.0404 - Accuracy: 0.6176 - F1: 0.5936
sub_29:Test (Best Model) - Loss: 0.9005 - Accuracy: 0.5797 - F1: 0.5629
sub_18:Test (Best Model) - Loss: 1.2431 - Accuracy: 0.4559 - F1: 0.3909
sub_1:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.7353 - F1: 0.7198
sub_16:Test (Best Model) - Loss: 0.9614 - Accuracy: 0.5588 - F1: 0.5176
sub_14:Test (Best Model) - Loss: 0.9162 - Accuracy: 0.6912 - F1: 0.6125
sub_28:Test (Best Model) - Loss: 1.7031 - Accuracy: 0.2794 - F1: 0.2282
sub_29:Test (Best Model) - Loss: 0.8614 - Accuracy: 0.6667 - F1: 0.6772
sub_13:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.5294 - F1: 0.4702
sub_21:Test (Best Model) - Loss: 0.7533 - Accuracy: 0.7206 - F1: 0.7044
sub_24:Test (Best Model) - Loss: 1.1636 - Accuracy: 0.3971 - F1: 0.4358
sub_19:Test (Best Model) - Loss: 1.0966 - Accuracy: 0.4118 - F1: 0.4304
sub_10:Test (Best Model) - Loss: 0.9560 - Accuracy: 0.6232 - F1: 0.6243
sub_3:Test (Best Model) - Loss: 0.8915 - Accuracy: 0.6522 - F1: 0.6546
sub_12:Test (Best Model) - Loss: 0.9015 - Accuracy: 0.6029 - F1: 0.6243
sub_18:Test (Best Model) - Loss: 0.9302 - Accuracy: 0.5588 - F1: 0.5303
sub_29:Test (Best Model) - Loss: 1.0170 - Accuracy: 0.5507 - F1: 0.5490
sub_24:Test (Best Model) - Loss: 0.9275 - Accuracy: 0.5735 - F1: 0.5777

=== Summary Results ===

acc: 59.19 ± 7.77
F1: 56.79 ± 8.55
acc-in: 85.58 ± 4.85
F1-in: 85.15 ± 5.18
