lr: 0.001
sub_2:Test (Best Model) - Loss: 1.4286 - Accuracy: 0.6232 - F1: 0.5397
sub_10:Test (Best Model) - Loss: 3.3817 - Accuracy: 0.5441 - F1: 0.5266
sub_3:Test (Best Model) - Loss: 2.1069 - Accuracy: 0.6618 - F1: 0.6230
sub_4:Test (Best Model) - Loss: 2.3987 - Accuracy: 0.5652 - F1: 0.5692
sub_8:Test (Best Model) - Loss: 2.9254 - Accuracy: 0.5735 - F1: 0.5442
sub_5:Test (Best Model) - Loss: 4.3816 - Accuracy: 0.4853 - F1: 0.4474
sub_13:Test (Best Model) - Loss: 1.4151 - Accuracy: 0.6765 - F1: 0.6189
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.7206 - F1: 0.7073
sub_9:Test (Best Model) - Loss: 2.2174 - Accuracy: 0.5000 - F1: 0.5396
sub_12:Test (Best Model) - Loss: 1.7603 - Accuracy: 0.6471 - F1: 0.6500
sub_6:Test (Best Model) - Loss: 3.6455 - Accuracy: 0.5147 - F1: 0.5155
sub_2:Test (Best Model) - Loss: 1.8971 - Accuracy: 0.6232 - F1: 0.5746
sub_15:Test (Best Model) - Loss: 3.0378 - Accuracy: 0.5735 - F1: 0.5896
sub_4:Test (Best Model) - Loss: 2.5295 - Accuracy: 0.5942 - F1: 0.5825
sub_10:Test (Best Model) - Loss: 3.1210 - Accuracy: 0.5294 - F1: 0.5387
sub_14:Test (Best Model) - Loss: 3.4641 - Accuracy: 0.4412 - F1: 0.3725
sub_5:Test (Best Model) - Loss: 3.3632 - Accuracy: 0.6029 - F1: 0.5795
sub_13:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.6176 - F1: 0.5557
sub_11:Test (Best Model) - Loss: 1.2814 - Accuracy: 0.8261 - F1: 0.8311
sub_8:Test (Best Model) - Loss: 2.6886 - Accuracy: 0.5882 - F1: 0.5587
sub_7:Test (Best Model) - Loss: 0.3213 - Accuracy: 0.9559 - F1: 0.9544
sub_9:Test (Best Model) - Loss: 0.7940 - Accuracy: 0.5735 - F1: 0.5266
sub_3:Test (Best Model) - Loss: 3.6426 - Accuracy: 0.5882 - F1: 0.5452
sub_15:Test (Best Model) - Loss: 1.6388 - Accuracy: 0.4706 - F1: 0.3809
sub_10:Test (Best Model) - Loss: 4.3248 - Accuracy: 0.4706 - F1: 0.4888
sub_2:Test (Best Model) - Loss: 1.4791 - Accuracy: 0.6232 - F1: 0.5594
sub_8:Test (Best Model) - Loss: 3.0483 - Accuracy: 0.6176 - F1: 0.5646
sub_7:Test (Best Model) - Loss: 1.9623 - Accuracy: 0.7647 - F1: 0.7645
sub_1:Test (Best Model) - Loss: 2.3924 - Accuracy: 0.6029 - F1: 0.5904
sub_6:Test (Best Model) - Loss: 4.5790 - Accuracy: 0.5441 - F1: 0.5164
sub_12:Test (Best Model) - Loss: 2.7369 - Accuracy: 0.6765 - F1: 0.6082
sub_3:Test (Best Model) - Loss: 1.2025 - Accuracy: 0.7794 - F1: 0.7790
sub_13:Test (Best Model) - Loss: 2.2967 - Accuracy: 0.4853 - F1: 0.4248
sub_10:Test (Best Model) - Loss: 5.4483 - Accuracy: 0.2941 - F1: 0.3237
sub_9:Test (Best Model) - Loss: 1.8154 - Accuracy: 0.6912 - F1: 0.6864
sub_11:Test (Best Model) - Loss: 3.3534 - Accuracy: 0.6087 - F1: 0.5473
sub_14:Test (Best Model) - Loss: 5.5227 - Accuracy: 0.4853 - F1: 0.4384
sub_5:Test (Best Model) - Loss: 3.9189 - Accuracy: 0.5294 - F1: 0.4881
sub_7:Test (Best Model) - Loss: 0.5088 - Accuracy: 0.8382 - F1: 0.8253
sub_15:Test (Best Model) - Loss: 4.0990 - Accuracy: 0.5000 - F1: 0.5419
sub_1:Test (Best Model) - Loss: 2.3645 - Accuracy: 0.5294 - F1: 0.5169
sub_3:Test (Best Model) - Loss: 1.4974 - Accuracy: 0.7059 - F1: 0.7055
sub_8:Test (Best Model) - Loss: 4.1516 - Accuracy: 0.5735 - F1: 0.5404
sub_4:Test (Best Model) - Loss: 2.0524 - Accuracy: 0.6812 - F1: 0.6932
sub_11:Test (Best Model) - Loss: 1.5682 - Accuracy: 0.7681 - F1: 0.7626
sub_14:Test (Best Model) - Loss: 5.3454 - Accuracy: 0.4412 - F1: 0.3668
sub_12:Test (Best Model) - Loss: 2.5692 - Accuracy: 0.6765 - F1: 0.6761
sub_5:Test (Best Model) - Loss: 2.6519 - Accuracy: 0.5441 - F1: 0.5270
sub_13:Test (Best Model) - Loss: 3.0881 - Accuracy: 0.3971 - F1: 0.3417
sub_2:Test (Best Model) - Loss: 1.5546 - Accuracy: 0.7391 - F1: 0.7275
sub_10:Test (Best Model) - Loss: 1.6878 - Accuracy: 0.5588 - F1: 0.5709
sub_11:Test (Best Model) - Loss: 1.8238 - Accuracy: 0.7391 - F1: 0.7289
sub_7:Test (Best Model) - Loss: 1.3497 - Accuracy: 0.7353 - F1: 0.7258
sub_6:Test (Best Model) - Loss: 2.9274 - Accuracy: 0.5294 - F1: 0.5129
sub_12:Test (Best Model) - Loss: 2.0025 - Accuracy: 0.6765 - F1: 0.6523
sub_8:Test (Best Model) - Loss: 1.8720 - Accuracy: 0.5735 - F1: 0.5370
sub_9:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.5588 - F1: 0.5487
sub_5:Test (Best Model) - Loss: 3.8975 - Accuracy: 0.6618 - F1: 0.5982
sub_14:Test (Best Model) - Loss: 4.9713 - Accuracy: 0.3971 - F1: 0.3341
sub_13:Test (Best Model) - Loss: 2.5434 - Accuracy: 0.4853 - F1: 0.4348
sub_3:Test (Best Model) - Loss: 4.4000 - Accuracy: 0.4559 - F1: 0.4520
sub_1:Test (Best Model) - Loss: 2.9163 - Accuracy: 0.5147 - F1: 0.5127
sub_15:Test (Best Model) - Loss: 2.2719 - Accuracy: 0.6618 - F1: 0.6595
sub_10:Test (Best Model) - Loss: 3.4581 - Accuracy: 0.5735 - F1: 0.5171
sub_7:Test (Best Model) - Loss: 1.2481 - Accuracy: 0.8382 - F1: 0.8332
sub_11:Test (Best Model) - Loss: 1.9769 - Accuracy: 0.6522 - F1: 0.6303
sub_2:Test (Best Model) - Loss: 2.7213 - Accuracy: 0.5217 - F1: 0.5254
sub_4:Test (Best Model) - Loss: 2.4802 - Accuracy: 0.5072 - F1: 0.4943
sub_5:Test (Best Model) - Loss: 1.8048 - Accuracy: 0.4265 - F1: 0.3528
sub_3:Test (Best Model) - Loss: 2.1579 - Accuracy: 0.6957 - F1: 0.6657
sub_12:Test (Best Model) - Loss: 1.4226 - Accuracy: 0.6912 - F1: 0.6702
sub_1:Test (Best Model) - Loss: 1.8866 - Accuracy: 0.5294 - F1: 0.4838
sub_11:Test (Best Model) - Loss: 2.1371 - Accuracy: 0.7536 - F1: 0.7166
sub_9:Test (Best Model) - Loss: 1.9036 - Accuracy: 0.7206 - F1: 0.7262
sub_8:Test (Best Model) - Loss: 2.7098 - Accuracy: 0.5441 - F1: 0.4732
sub_13:Test (Best Model) - Loss: 3.5216 - Accuracy: 0.5652 - F1: 0.5350
sub_14:Test (Best Model) - Loss: 6.5619 - Accuracy: 0.3529 - F1: 0.3052
sub_10:Test (Best Model) - Loss: 2.4193 - Accuracy: 0.2059 - F1: 0.0875
sub_3:Test (Best Model) - Loss: 2.5503 - Accuracy: 0.6812 - F1: 0.6184
sub_6:Test (Best Model) - Loss: 4.3602 - Accuracy: 0.4265 - F1: 0.3431
sub_4:Test (Best Model) - Loss: 3.2580 - Accuracy: 0.5797 - F1: 0.5446
sub_7:Test (Best Model) - Loss: 2.8662 - Accuracy: 0.6324 - F1: 0.5847
sub_15:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.7794 - F1: 0.7889
sub_5:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.4118 - F1: 0.3370
sub_2:Test (Best Model) - Loss: 1.8753 - Accuracy: 0.7647 - F1: 0.7438
sub_3:Test (Best Model) - Loss: 3.1924 - Accuracy: 0.5652 - F1: 0.5581
sub_4:Test (Best Model) - Loss: 0.3962 - Accuracy: 0.8116 - F1: 0.7894
sub_11:Test (Best Model) - Loss: 3.6680 - Accuracy: 0.5942 - F1: 0.5597
sub_7:Test (Best Model) - Loss: 3.1284 - Accuracy: 0.5000 - F1: 0.4605
sub_14:Test (Best Model) - Loss: 1.0195 - Accuracy: 0.6912 - F1: 0.6352
sub_10:Test (Best Model) - Loss: 2.9481 - Accuracy: 0.5294 - F1: 0.4808
sub_9:Test (Best Model) - Loss: 3.1787 - Accuracy: 0.5882 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 2.3950 - Accuracy: 0.7101 - F1: 0.7268
sub_1:Test (Best Model) - Loss: 1.5541 - Accuracy: 0.6812 - F1: 0.6754
sub_3:Test (Best Model) - Loss: 1.2338 - Accuracy: 0.6812 - F1: 0.6496
sub_15:Test (Best Model) - Loss: 1.2129 - Accuracy: 0.6176 - F1: 0.5692
sub_11:Test (Best Model) - Loss: 2.1005 - Accuracy: 0.5217 - F1: 0.4250
sub_8:Test (Best Model) - Loss: 2.9567 - Accuracy: 0.6765 - F1: 0.6101
sub_6:Test (Best Model) - Loss: 3.9697 - Accuracy: 0.5441 - F1: 0.5678
sub_7:Test (Best Model) - Loss: 3.0786 - Accuracy: 0.6471 - F1: 0.5684
sub_5:Test (Best Model) - Loss: 0.9445 - Accuracy: 0.4853 - F1: 0.3540
sub_13:Test (Best Model) - Loss: 4.2775 - Accuracy: 0.4493 - F1: 0.4279
sub_2:Test (Best Model) - Loss: 1.9472 - Accuracy: 0.7059 - F1: 0.6498
sub_4:Test (Best Model) - Loss: 1.9559 - Accuracy: 0.6522 - F1: 0.6540
sub_15:Test (Best Model) - Loss: 2.6277 - Accuracy: 0.4559 - F1: 0.3393
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.5217 - F1: 0.4790
sub_14:Test (Best Model) - Loss: 5.1964 - Accuracy: 0.3971 - F1: 0.3906
sub_7:Test (Best Model) - Loss: 3.3880 - Accuracy: 0.6471 - F1: 0.5852
sub_11:Test (Best Model) - Loss: 0.9971 - Accuracy: 0.8261 - F1: 0.8253
sub_9:Test (Best Model) - Loss: 4.5283 - Accuracy: 0.5735 - F1: 0.5042
sub_3:Test (Best Model) - Loss: 3.2827 - Accuracy: 0.7246 - F1: 0.6789
sub_6:Test (Best Model) - Loss: 1.7397 - Accuracy: 0.5942 - F1: 0.6082
sub_5:Test (Best Model) - Loss: 1.1566 - Accuracy: 0.6618 - F1: 0.5927
sub_10:Test (Best Model) - Loss: 2.4993 - Accuracy: 0.5735 - F1: 0.5255
sub_13:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.4638 - F1: 0.4694
sub_1:Test (Best Model) - Loss: 1.0078 - Accuracy: 0.5797 - F1: 0.5306
sub_15:Test (Best Model) - Loss: 0.7867 - Accuracy: 0.7500 - F1: 0.7592
sub_2:Test (Best Model) - Loss: 0.9497 - Accuracy: 0.7794 - F1: 0.7734
sub_14:Test (Best Model) - Loss: 3.8965 - Accuracy: 0.4265 - F1: 0.4250
sub_8:Test (Best Model) - Loss: 2.0029 - Accuracy: 0.7353 - F1: 0.6842
sub_12:Test (Best Model) - Loss: 1.4406 - Accuracy: 0.7681 - F1: 0.7762
sub_7:Test (Best Model) - Loss: 2.6951 - Accuracy: 0.5441 - F1: 0.4002
sub_10:Test (Best Model) - Loss: 3.0841 - Accuracy: 0.4412 - F1: 0.3519
sub_11:Test (Best Model) - Loss: 1.5067 - Accuracy: 0.8261 - F1: 0.8273
sub_4:Test (Best Model) - Loss: 1.2868 - Accuracy: 0.7826 - F1: 0.7904
sub_12:Test (Best Model) - Loss: 1.4197 - Accuracy: 0.7391 - F1: 0.7264
sub_7:Test (Best Model) - Loss: 3.9934 - Accuracy: 0.6029 - F1: 0.5712
sub_5:Test (Best Model) - Loss: 3.3548 - Accuracy: 0.5147 - F1: 0.4799
sub_3:Test (Best Model) - Loss: 3.3277 - Accuracy: 0.6957 - F1: 0.6604
sub_9:Test (Best Model) - Loss: 1.1808 - Accuracy: 0.7647 - F1: 0.7651
sub_1:Test (Best Model) - Loss: 1.4221 - Accuracy: 0.7246 - F1: 0.7442
sub_15:Test (Best Model) - Loss: 1.8033 - Accuracy: 0.6471 - F1: 0.6641
sub_8:Test (Best Model) - Loss: 2.3224 - Accuracy: 0.7059 - F1: 0.6443
sub_2:Test (Best Model) - Loss: 1.5022 - Accuracy: 0.7647 - F1: 0.7444
sub_11:Test (Best Model) - Loss: 2.1826 - Accuracy: 0.6667 - F1: 0.6626
sub_13:Test (Best Model) - Loss: 4.2396 - Accuracy: 0.5072 - F1: 0.4886
sub_6:Test (Best Model) - Loss: 2.5277 - Accuracy: 0.6377 - F1: 0.5806
sub_12:Test (Best Model) - Loss: 0.9189 - Accuracy: 0.7101 - F1: 0.7201
sub_14:Test (Best Model) - Loss: 4.3488 - Accuracy: 0.4853 - F1: 0.4617
sub_10:Test (Best Model) - Loss: 3.8430 - Accuracy: 0.6522 - F1: 0.6057
sub_1:Test (Best Model) - Loss: 2.1511 - Accuracy: 0.4638 - F1: 0.4101
sub_7:Test (Best Model) - Loss: 2.2207 - Accuracy: 0.7794 - F1: 0.7805
sub_11:Test (Best Model) - Loss: 2.5103 - Accuracy: 0.6957 - F1: 0.6939
sub_3:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.7391 - F1: 0.7083
sub_9:Test (Best Model) - Loss: 4.9402 - Accuracy: 0.5000 - F1: 0.4362
sub_4:Test (Best Model) - Loss: 1.9041 - Accuracy: 0.7246 - F1: 0.7043
sub_14:Test (Best Model) - Loss: 3.2618 - Accuracy: 0.3529 - F1: 0.3938
sub_5:Test (Best Model) - Loss: 4.0688 - Accuracy: 0.6324 - F1: 0.5678
sub_13:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.3188 - F1: 0.2587
sub_8:Test (Best Model) - Loss: 0.7894 - Accuracy: 0.6471 - F1: 0.6328
sub_15:Test (Best Model) - Loss: 1.3328 - Accuracy: 0.6618 - F1: 0.6184
sub_1:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.7941 - F1: 0.7893
sub_11:Test (Best Model) - Loss: 1.7516 - Accuracy: 0.6667 - F1: 0.6202
sub_2:Test (Best Model) - Loss: 1.5141 - Accuracy: 0.7500 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.9358 - Accuracy: 0.6232 - F1: 0.5585
sub_7:Test (Best Model) - Loss: 3.4227 - Accuracy: 0.5147 - F1: 0.5068
sub_10:Test (Best Model) - Loss: 3.2019 - Accuracy: 0.6232 - F1: 0.5678
sub_3:Test (Best Model) - Loss: 2.8199 - Accuracy: 0.7246 - F1: 0.7216
sub_12:Test (Best Model) - Loss: 2.4628 - Accuracy: 0.6522 - F1: 0.6380
sub_1:Test (Best Model) - Loss: 2.3874 - Accuracy: 0.7353 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 1.6758 - Accuracy: 0.7206 - F1: 0.7219
sub_9:Test (Best Model) - Loss: 1.1804 - Accuracy: 0.7353 - F1: 0.7198
sub_7:Test (Best Model) - Loss: 2.0791 - Accuracy: 0.6912 - F1: 0.6834
sub_4:Test (Best Model) - Loss: 1.6357 - Accuracy: 0.7681 - F1: 0.7486
sub_10:Test (Best Model) - Loss: 1.2299 - Accuracy: 0.6667 - F1: 0.6631
sub_11:Test (Best Model) - Loss: 2.4027 - Accuracy: 0.7101 - F1: 0.7127
sub_8:Test (Best Model) - Loss: 3.8498 - Accuracy: 0.5735 - F1: 0.5534
sub_3:Test (Best Model) - Loss: 1.9577 - Accuracy: 0.6667 - F1: 0.6725
sub_5:Test (Best Model) - Loss: 3.4587 - Accuracy: 0.5588 - F1: 0.4906
sub_15:Test (Best Model) - Loss: 3.8016 - Accuracy: 0.4853 - F1: 0.3987
sub_1:Test (Best Model) - Loss: 2.4165 - Accuracy: 0.7500 - F1: 0.6871
sub_12:Test (Best Model) - Loss: 4.6722 - Accuracy: 0.4706 - F1: 0.3786
sub_14:Test (Best Model) - Loss: 0.9152 - Accuracy: 0.6912 - F1: 0.6986
sub_6:Test (Best Model) - Loss: 2.0194 - Accuracy: 0.6522 - F1: 0.5951
sub_13:Test (Best Model) - Loss: 5.1659 - Accuracy: 0.4559 - F1: 0.3615
sub_2:Test (Best Model) - Loss: 1.7429 - Accuracy: 0.6377 - F1: 0.5873
sub_4:Test (Best Model) - Loss: 3.0804 - Accuracy: 0.4928 - F1: 0.4653
sub_9:Test (Best Model) - Loss: 3.5575 - Accuracy: 0.4853 - F1: 0.3962
sub_8:Test (Best Model) - Loss: 1.5238 - Accuracy: 0.5882 - F1: 0.6189
sub_5:Test (Best Model) - Loss: 2.1119 - Accuracy: 0.6912 - F1: 0.6169
sub_3:Test (Best Model) - Loss: 1.0555 - Accuracy: 0.8406 - F1: 0.8353
sub_15:Test (Best Model) - Loss: 1.2045 - Accuracy: 0.6029 - F1: 0.5751
sub_1:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.6618 - F1: 0.6187
sub_11:Test (Best Model) - Loss: 2.4448 - Accuracy: 0.6522 - F1: 0.6361
sub_10:Test (Best Model) - Loss: 2.2452 - Accuracy: 0.6957 - F1: 0.6706
sub_12:Test (Best Model) - Loss: 1.3203 - Accuracy: 0.8235 - F1: 0.8240
sub_6:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.5797 - F1: 0.5334
sub_7:Test (Best Model) - Loss: 3.7555 - Accuracy: 0.6471 - F1: 0.5729
sub_14:Test (Best Model) - Loss: 0.8223 - Accuracy: 0.8529 - F1: 0.8599
sub_8:Test (Best Model) - Loss: 4.3921 - Accuracy: 0.4853 - F1: 0.5134
sub_5:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.8088 - F1: 0.7973
sub_9:Test (Best Model) - Loss: 2.3536 - Accuracy: 0.4559 - F1: 0.4863
sub_2:Test (Best Model) - Loss: 2.9242 - Accuracy: 0.4783 - F1: 0.4041
sub_10:Test (Best Model) - Loss: 2.8492 - Accuracy: 0.6667 - F1: 0.6534
sub_4:Test (Best Model) - Loss: 1.1248 - Accuracy: 0.6522 - F1: 0.5750
sub_14:Test (Best Model) - Loss: 0.8018 - Accuracy: 0.8088 - F1: 0.8173
sub_15:Test (Best Model) - Loss: 4.8115 - Accuracy: 0.3971 - F1: 0.3665
sub_13:Test (Best Model) - Loss: 2.9861 - Accuracy: 0.3676 - F1: 0.2986
sub_12:Test (Best Model) - Loss: 3.2295 - Accuracy: 0.5588 - F1: 0.5242
sub_5:Test (Best Model) - Loss: 1.7836 - Accuracy: 0.6765 - F1: 0.6342
sub_6:Test (Best Model) - Loss: 2.8159 - Accuracy: 0.5797 - F1: 0.5341
sub_1:Test (Best Model) - Loss: 1.4828 - Accuracy: 0.8088 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.6232 - F1: 0.5714
sub_8:Test (Best Model) - Loss: 4.3706 - Accuracy: 0.6176 - F1: 0.5693
sub_2:Test (Best Model) - Loss: 1.7549 - Accuracy: 0.4928 - F1: 0.4908
sub_13:Test (Best Model) - Loss: 1.4842 - Accuracy: 0.5588 - F1: 0.5347
sub_15:Test (Best Model) - Loss: 4.3331 - Accuracy: 0.5294 - F1: 0.4552
sub_12:Test (Best Model) - Loss: 0.9546 - Accuracy: 0.7941 - F1: 0.7863
sub_4:Test (Best Model) - Loss: 1.6241 - Accuracy: 0.6232 - F1: 0.5601
sub_8:Test (Best Model) - Loss: 4.0428 - Accuracy: 0.4559 - F1: 0.4750
sub_14:Test (Best Model) - Loss: 1.4239 - Accuracy: 0.7353 - F1: 0.7112
sub_9:Test (Best Model) - Loss: 3.4361 - Accuracy: 0.5147 - F1: 0.4903
sub_6:Test (Best Model) - Loss: 1.1360 - Accuracy: 0.7101 - F1: 0.6583
sub_12:Test (Best Model) - Loss: 1.4249 - Accuracy: 0.6912 - F1: 0.7022
sub_2:Test (Best Model) - Loss: 1.5747 - Accuracy: 0.6087 - F1: 0.5313
sub_4:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.6087 - F1: 0.5446
sub_13:Test (Best Model) - Loss: 4.0479 - Accuracy: 0.4853 - F1: 0.3895
sub_15:Test (Best Model) - Loss: 2.9691 - Accuracy: 0.5882 - F1: 0.5388
sub_13:Test (Best Model) - Loss: 1.4798 - Accuracy: 0.6176 - F1: 0.5494
sub_6:Test (Best Model) - Loss: 2.3425 - Accuracy: 0.5942 - F1: 0.5489
sub_2:Test (Best Model) - Loss: 3.4644 - Accuracy: 0.6232 - F1: 0.6277
sub_9:Test (Best Model) - Loss: 2.9024 - Accuracy: 0.5441 - F1: 0.5114
sub_6:Test (Best Model) - Loss: 2.4363 - Accuracy: 0.6087 - F1: 0.5448
sub_9:Test (Best Model) - Loss: 2.0611 - Accuracy: 0.6471 - F1: 0.6511
sub_6:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.6667 - F1: 0.5898
sub_22:Test (Best Model) - Loss: 2.6491 - Accuracy: 0.5441 - F1: 0.4884
sub_21:Test (Best Model) - Loss: 1.6935 - Accuracy: 0.7794 - F1: 0.7802
sub_20:Test (Best Model) - Loss: 2.8252 - Accuracy: 0.5147 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 1.7221 - Accuracy: 0.5147 - F1: 0.4836
sub_17:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.5652 - F1: 0.5327
sub_27:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.5652 - F1: 0.5327
sub_24:Test (Best Model) - Loss: 2.5163 - Accuracy: 0.5735 - F1: 0.5026
sub_25:Test (Best Model) - Loss: 0.8365 - Accuracy: 0.8696 - F1: 0.8642
sub_18:Test (Best Model) - Loss: 2.7663 - Accuracy: 0.5652 - F1: 0.5256
sub_22:Test (Best Model) - Loss: 2.1919 - Accuracy: 0.6471 - F1: 0.6148
sub_20:Test (Best Model) - Loss: 1.1791 - Accuracy: 0.6618 - F1: 0.6432
sub_26:Test (Best Model) - Loss: 2.3171 - Accuracy: 0.6667 - F1: 0.6708
sub_28:Test (Best Model) - Loss: 1.5157 - Accuracy: 0.4265 - F1: 0.3819
sub_19:Test (Best Model) - Loss: 5.1012 - Accuracy: 0.3676 - F1: 0.3523
sub_16:Test (Best Model) - Loss: 3.2362 - Accuracy: 0.6176 - F1: 0.6247
sub_23:Test (Best Model) - Loss: 3.1172 - Accuracy: 0.5507 - F1: 0.4951
sub_29:Test (Best Model) - Loss: 2.8415 - Accuracy: 0.4706 - F1: 0.5018
sub_21:Test (Best Model) - Loss: 1.5406 - Accuracy: 0.7500 - F1: 0.7410
sub_24:Test (Best Model) - Loss: 4.8365 - Accuracy: 0.4265 - F1: 0.4343
sub_25:Test (Best Model) - Loss: 0.3770 - Accuracy: 0.9275 - F1: 0.9296
sub_23:Test (Best Model) - Loss: 2.5458 - Accuracy: 0.6667 - F1: 0.6122
sub_21:Test (Best Model) - Loss: 1.8321 - Accuracy: 0.7794 - F1: 0.7861
sub_17:Test (Best Model) - Loss: 1.3335 - Accuracy: 0.7971 - F1: 0.7819
sub_27:Test (Best Model) - Loss: 1.3335 - Accuracy: 0.7971 - F1: 0.7819
sub_29:Test (Best Model) - Loss: 4.7512 - Accuracy: 0.4706 - F1: 0.4775
sub_16:Test (Best Model) - Loss: 2.4460 - Accuracy: 0.7206 - F1: 0.6997
sub_18:Test (Best Model) - Loss: 3.2878 - Accuracy: 0.5797 - F1: 0.5490
sub_22:Test (Best Model) - Loss: 2.4594 - Accuracy: 0.6471 - F1: 0.6217
sub_23:Test (Best Model) - Loss: 1.2436 - Accuracy: 0.7971 - F1: 0.7983
sub_20:Test (Best Model) - Loss: 1.4515 - Accuracy: 0.7206 - F1: 0.6905
sub_24:Test (Best Model) - Loss: 4.1056 - Accuracy: 0.5441 - F1: 0.5420
sub_26:Test (Best Model) - Loss: 2.0140 - Accuracy: 0.8116 - F1: 0.8074
sub_28:Test (Best Model) - Loss: 2.1329 - Accuracy: 0.5441 - F1: 0.4769
sub_17:Test (Best Model) - Loss: 2.0929 - Accuracy: 0.5942 - F1: 0.5759
sub_19:Test (Best Model) - Loss: 5.2485 - Accuracy: 0.3971 - F1: 0.3349
sub_27:Test (Best Model) - Loss: 2.0929 - Accuracy: 0.5942 - F1: 0.5759
sub_16:Test (Best Model) - Loss: 4.1109 - Accuracy: 0.5147 - F1: 0.5098
sub_21:Test (Best Model) - Loss: 1.7196 - Accuracy: 0.8382 - F1: 0.8322
sub_25:Test (Best Model) - Loss: 0.2431 - Accuracy: 0.9565 - F1: 0.9523
sub_24:Test (Best Model) - Loss: 3.0626 - Accuracy: 0.6324 - F1: 0.5919
sub_19:Test (Best Model) - Loss: 5.3049 - Accuracy: 0.4706 - F1: 0.4390
sub_16:Test (Best Model) - Loss: 3.8634 - Accuracy: 0.6765 - F1: 0.6357
sub_23:Test (Best Model) - Loss: 0.9329 - Accuracy: 0.8406 - F1: 0.8276
sub_18:Test (Best Model) - Loss: 2.6256 - Accuracy: 0.6377 - F1: 0.6256
sub_17:Test (Best Model) - Loss: 0.9405 - Accuracy: 0.6812 - F1: 0.6599
sub_29:Test (Best Model) - Loss: 3.1304 - Accuracy: 0.4706 - F1: 0.4944
sub_22:Test (Best Model) - Loss: 2.7018 - Accuracy: 0.5735 - F1: 0.5197
sub_25:Test (Best Model) - Loss: 1.5402 - Accuracy: 0.8261 - F1: 0.8269
sub_27:Test (Best Model) - Loss: 0.9405 - Accuracy: 0.6812 - F1: 0.6599
sub_21:Test (Best Model) - Loss: 1.3231 - Accuracy: 0.4706 - F1: 0.4220
sub_26:Test (Best Model) - Loss: 4.3146 - Accuracy: 0.6087 - F1: 0.5811
sub_20:Test (Best Model) - Loss: 2.7097 - Accuracy: 0.5735 - F1: 0.5365
sub_19:Test (Best Model) - Loss: 4.9397 - Accuracy: 0.4265 - F1: 0.3760
sub_28:Test (Best Model) - Loss: 2.7935 - Accuracy: 0.5588 - F1: 0.5270
sub_16:Test (Best Model) - Loss: 2.9012 - Accuracy: 0.5588 - F1: 0.5011
sub_23:Test (Best Model) - Loss: 1.2537 - Accuracy: 0.8116 - F1: 0.8051
sub_24:Test (Best Model) - Loss: 5.2168 - Accuracy: 0.5000 - F1: 0.4986
sub_21:Test (Best Model) - Loss: 1.1693 - Accuracy: 0.7794 - F1: 0.7645
sub_26:Test (Best Model) - Loss: 3.6430 - Accuracy: 0.5942 - F1: 0.5608
sub_29:Test (Best Model) - Loss: 2.4880 - Accuracy: 0.4706 - F1: 0.4651
sub_19:Test (Best Model) - Loss: 6.0300 - Accuracy: 0.3824 - F1: 0.3337
sub_22:Test (Best Model) - Loss: 3.2134 - Accuracy: 0.5147 - F1: 0.4904
sub_28:Test (Best Model) - Loss: 1.1567 - Accuracy: 0.6912 - F1: 0.6721
sub_18:Test (Best Model) - Loss: 2.2729 - Accuracy: 0.6522 - F1: 0.6503
sub_16:Test (Best Model) - Loss: 2.9057 - Accuracy: 0.6765 - F1: 0.6785
sub_24:Test (Best Model) - Loss: 1.5557 - Accuracy: 0.6324 - F1: 0.6107
sub_25:Test (Best Model) - Loss: 0.5267 - Accuracy: 0.9420 - F1: 0.9384
sub_29:Test (Best Model) - Loss: 1.2728 - Accuracy: 0.5294 - F1: 0.4937
sub_20:Test (Best Model) - Loss: 2.8642 - Accuracy: 0.5000 - F1: 0.4536
sub_22:Test (Best Model) - Loss: 4.8150 - Accuracy: 0.5652 - F1: 0.5347
sub_17:Test (Best Model) - Loss: 1.5681 - Accuracy: 0.7246 - F1: 0.7312
sub_23:Test (Best Model) - Loss: 5.1667 - Accuracy: 0.4265 - F1: 0.4184
sub_27:Test (Best Model) - Loss: 1.5681 - Accuracy: 0.7246 - F1: 0.7312
sub_21:Test (Best Model) - Loss: 1.0992 - Accuracy: 0.8235 - F1: 0.8155
sub_25:Test (Best Model) - Loss: 1.9228 - Accuracy: 0.7353 - F1: 0.7227
sub_29:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.6765 - F1: 0.6224
sub_19:Test (Best Model) - Loss: 3.0064 - Accuracy: 0.6471 - F1: 0.6590
sub_26:Test (Best Model) - Loss: 1.5012 - Accuracy: 0.6667 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 3.7403 - Accuracy: 0.5942 - F1: 0.5954
sub_28:Test (Best Model) - Loss: 1.6442 - Accuracy: 0.6029 - F1: 0.5611
sub_16:Test (Best Model) - Loss: 3.3229 - Accuracy: 0.5588 - F1: 0.5836
sub_20:Test (Best Model) - Loss: 0.9589 - Accuracy: 0.6765 - F1: 0.6051
sub_24:Test (Best Model) - Loss: 1.9110 - Accuracy: 0.6912 - F1: 0.6559
sub_17:Test (Best Model) - Loss: 2.3563 - Accuracy: 0.6232 - F1: 0.6022
sub_29:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.7059 - F1: 0.6460
sub_25:Test (Best Model) - Loss: 5.2846 - Accuracy: 0.5882 - F1: 0.5698
sub_21:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.8088 - F1: 0.7958
sub_27:Test (Best Model) - Loss: 2.3563 - Accuracy: 0.6232 - F1: 0.6022
sub_22:Test (Best Model) - Loss: 4.7230 - Accuracy: 0.5072 - F1: 0.4517
sub_28:Test (Best Model) - Loss: 2.2327 - Accuracy: 0.3971 - F1: 0.2775
sub_23:Test (Best Model) - Loss: 2.9618 - Accuracy: 0.5588 - F1: 0.4865
sub_20:Test (Best Model) - Loss: 2.1173 - Accuracy: 0.5588 - F1: 0.4735
sub_25:Test (Best Model) - Loss: 2.7542 - Accuracy: 0.6912 - F1: 0.6508
sub_16:Test (Best Model) - Loss: 1.4487 - Accuracy: 0.7353 - F1: 0.7095
sub_18:Test (Best Model) - Loss: 2.6721 - Accuracy: 0.4706 - F1: 0.5113
sub_26:Test (Best Model) - Loss: 3.8069 - Accuracy: 0.5294 - F1: 0.4828
sub_24:Test (Best Model) - Loss: 2.3246 - Accuracy: 0.7353 - F1: 0.6972
sub_19:Test (Best Model) - Loss: 2.0325 - Accuracy: 0.5735 - F1: 0.5113
sub_17:Test (Best Model) - Loss: 2.8795 - Accuracy: 0.4348 - F1: 0.4417
sub_22:Test (Best Model) - Loss: 3.9153 - Accuracy: 0.6087 - F1: 0.6085
sub_28:Test (Best Model) - Loss: 4.0914 - Accuracy: 0.3824 - F1: 0.2682
sub_21:Test (Best Model) - Loss: 0.8522 - Accuracy: 0.6471 - F1: 0.5791
sub_27:Test (Best Model) - Loss: 2.8795 - Accuracy: 0.4348 - F1: 0.4417
sub_20:Test (Best Model) - Loss: 1.0695 - Accuracy: 0.5294 - F1: 0.3990
sub_25:Test (Best Model) - Loss: 4.4383 - Accuracy: 0.6029 - F1: 0.6054
sub_16:Test (Best Model) - Loss: 3.1148 - Accuracy: 0.6176 - F1: 0.5751
sub_24:Test (Best Model) - Loss: 2.3476 - Accuracy: 0.5735 - F1: 0.5413
sub_26:Test (Best Model) - Loss: 1.0652 - Accuracy: 0.5147 - F1: 0.4855
sub_23:Test (Best Model) - Loss: 7.0981 - Accuracy: 0.3382 - F1: 0.2970
sub_29:Test (Best Model) - Loss: 2.8214 - Accuracy: 0.6765 - F1: 0.6873
sub_22:Test (Best Model) - Loss: 1.1901 - Accuracy: 0.4638 - F1: 0.3811
sub_25:Test (Best Model) - Loss: 3.6503 - Accuracy: 0.7059 - F1: 0.7096
sub_18:Test (Best Model) - Loss: 2.8515 - Accuracy: 0.4853 - F1: 0.5166
sub_19:Test (Best Model) - Loss: 2.5608 - Accuracy: 0.6618 - F1: 0.6807
sub_17:Test (Best Model) - Loss: 4.0933 - Accuracy: 0.4348 - F1: 0.4244
sub_21:Test (Best Model) - Loss: 1.1824 - Accuracy: 0.6176 - F1: 0.5100
sub_16:Test (Best Model) - Loss: 2.2267 - Accuracy: 0.6471 - F1: 0.6438
sub_27:Test (Best Model) - Loss: 4.0933 - Accuracy: 0.4348 - F1: 0.4244
sub_20:Test (Best Model) - Loss: 1.2317 - Accuracy: 0.7647 - F1: 0.7429
sub_29:Test (Best Model) - Loss: 0.7677 - Accuracy: 0.5588 - F1: 0.5114
sub_28:Test (Best Model) - Loss: 4.6928 - Accuracy: 0.3382 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 2.2189 - Accuracy: 0.5072 - F1: 0.4967
sub_25:Test (Best Model) - Loss: 2.5101 - Accuracy: 0.6765 - F1: 0.6689
sub_22:Test (Best Model) - Loss: 3.8109 - Accuracy: 0.5217 - F1: 0.5488
sub_21:Test (Best Model) - Loss: 2.9991 - Accuracy: 0.6029 - F1: 0.5478
sub_27:Test (Best Model) - Loss: 2.2189 - Accuracy: 0.5072 - F1: 0.4967
sub_23:Test (Best Model) - Loss: 3.0100 - Accuracy: 0.4412 - F1: 0.3785
sub_24:Test (Best Model) - Loss: 2.8618 - Accuracy: 0.6618 - F1: 0.5929
sub_20:Test (Best Model) - Loss: 0.8708 - Accuracy: 0.6176 - F1: 0.5795
sub_19:Test (Best Model) - Loss: 2.7194 - Accuracy: 0.6176 - F1: 0.6421
sub_16:Test (Best Model) - Loss: 4.2247 - Accuracy: 0.4118 - F1: 0.3531
sub_29:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.4706 - F1: 0.3619
sub_18:Test (Best Model) - Loss: 4.0265 - Accuracy: 0.5294 - F1: 0.5645
sub_26:Test (Best Model) - Loss: 3.8034 - Accuracy: 0.4706 - F1: 0.4282
sub_25:Test (Best Model) - Loss: 4.2916 - Accuracy: 0.6324 - F1: 0.6117
sub_16:Test (Best Model) - Loss: 3.6833 - Accuracy: 0.5147 - F1: 0.4394
sub_28:Test (Best Model) - Loss: 4.8488 - Accuracy: 0.3824 - F1: 0.3708
sub_20:Test (Best Model) - Loss: 1.2166 - Accuracy: 0.6957 - F1: 0.6761
sub_21:Test (Best Model) - Loss: 2.7330 - Accuracy: 0.7500 - F1: 0.7062
sub_18:Test (Best Model) - Loss: 3.4078 - Accuracy: 0.5441 - F1: 0.5580
sub_23:Test (Best Model) - Loss: 4.3225 - Accuracy: 0.5147 - F1: 0.4634
sub_25:Test (Best Model) - Loss: 2.9784 - Accuracy: 0.7500 - F1: 0.7607
sub_22:Test (Best Model) - Loss: 2.3003 - Accuracy: 0.6912 - F1: 0.6901
sub_24:Test (Best Model) - Loss: 1.2141 - Accuracy: 0.8088 - F1: 0.8135
sub_17:Test (Best Model) - Loss: 3.9269 - Accuracy: 0.6087 - F1: 0.5974
sub_19:Test (Best Model) - Loss: 2.4809 - Accuracy: 0.5147 - F1: 0.4979
sub_26:Test (Best Model) - Loss: 3.6374 - Accuracy: 0.5588 - F1: 0.5522
sub_27:Test (Best Model) - Loss: 3.9269 - Accuracy: 0.6087 - F1: 0.5974
sub_29:Test (Best Model) - Loss: 2.8731 - Accuracy: 0.6377 - F1: 0.5831
sub_16:Test (Best Model) - Loss: 4.1126 - Accuracy: 0.4412 - F1: 0.4406
sub_21:Test (Best Model) - Loss: 1.8303 - Accuracy: 0.7353 - F1: 0.6753
sub_24:Test (Best Model) - Loss: 3.8473 - Accuracy: 0.4559 - F1: 0.3585
sub_23:Test (Best Model) - Loss: 1.7864 - Accuracy: 0.3768 - F1: 0.2878
sub_18:Test (Best Model) - Loss: 4.4040 - Accuracy: 0.5588 - F1: 0.5998
sub_25:Test (Best Model) - Loss: 3.3351 - Accuracy: 0.6912 - F1: 0.6506
sub_17:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.5882 - F1: 0.6047
sub_28:Test (Best Model) - Loss: 4.8734 - Accuracy: 0.4559 - F1: 0.3657
sub_19:Test (Best Model) - Loss: 3.1305 - Accuracy: 0.5882 - F1: 0.5397
sub_27:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.5882 - F1: 0.6047
sub_20:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.6957 - F1: 0.7006
sub_16:Test (Best Model) - Loss: 4.1388 - Accuracy: 0.4559 - F1: 0.3884
sub_22:Test (Best Model) - Loss: 1.9139 - Accuracy: 0.6471 - F1: 0.6202
sub_17:Test (Best Model) - Loss: 3.2457 - Accuracy: 0.6618 - F1: 0.6270
sub_21:Test (Best Model) - Loss: 0.9793 - Accuracy: 0.7059 - F1: 0.6644
sub_26:Test (Best Model) - Loss: 2.9868 - Accuracy: 0.6618 - F1: 0.6335
sub_27:Test (Best Model) - Loss: 3.2457 - Accuracy: 0.6618 - F1: 0.6270
sub_20:Test (Best Model) - Loss: 1.6507 - Accuracy: 0.6377 - F1: 0.6335
sub_29:Test (Best Model) - Loss: 3.3266 - Accuracy: 0.7246 - F1: 0.6671
sub_23:Test (Best Model) - Loss: 3.8586 - Accuracy: 0.4638 - F1: 0.4063
sub_18:Test (Best Model) - Loss: 3.1570 - Accuracy: 0.6176 - F1: 0.5995
sub_24:Test (Best Model) - Loss: 1.9765 - Accuracy: 0.7647 - F1: 0.7641
sub_19:Test (Best Model) - Loss: 2.6316 - Accuracy: 0.4265 - F1: 0.3546
sub_25:Test (Best Model) - Loss: 3.6815 - Accuracy: 0.6912 - F1: 0.6698
sub_26:Test (Best Model) - Loss: 1.9535 - Accuracy: 0.4265 - F1: 0.3450
sub_28:Test (Best Model) - Loss: 4.4560 - Accuracy: 0.4265 - F1: 0.3045
sub_17:Test (Best Model) - Loss: 3.6356 - Accuracy: 0.5441 - F1: 0.5236
sub_20:Test (Best Model) - Loss: 0.7938 - Accuracy: 0.6957 - F1: 0.6889
sub_21:Test (Best Model) - Loss: 2.6227 - Accuracy: 0.7059 - F1: 0.6462
sub_22:Test (Best Model) - Loss: 3.0986 - Accuracy: 0.6176 - F1: 0.6121
sub_27:Test (Best Model) - Loss: 3.6356 - Accuracy: 0.5441 - F1: 0.5236
sub_18:Test (Best Model) - Loss: 3.3229 - Accuracy: 0.3971 - F1: 0.3838
sub_24:Test (Best Model) - Loss: 1.6743 - Accuracy: 0.7941 - F1: 0.8001
sub_17:Test (Best Model) - Loss: 1.2724 - Accuracy: 0.5588 - F1: 0.5513
sub_23:Test (Best Model) - Loss: 3.6694 - Accuracy: 0.5072 - F1: 0.4852
sub_29:Test (Best Model) - Loss: 2.2311 - Accuracy: 0.5942 - F1: 0.5447
sub_19:Test (Best Model) - Loss: 3.2154 - Accuracy: 0.5294 - F1: 0.4986
sub_28:Test (Best Model) - Loss: 4.8977 - Accuracy: 0.3676 - F1: 0.2710
sub_27:Test (Best Model) - Loss: 1.2724 - Accuracy: 0.5588 - F1: 0.5513
sub_26:Test (Best Model) - Loss: 2.5149 - Accuracy: 0.4265 - F1: 0.3776
sub_24:Test (Best Model) - Loss: 1.0087 - Accuracy: 0.7647 - F1: 0.7815
sub_17:Test (Best Model) - Loss: 4.5941 - Accuracy: 0.3382 - F1: 0.3362
sub_20:Test (Best Model) - Loss: 0.9871 - Accuracy: 0.7246 - F1: 0.7249
sub_23:Test (Best Model) - Loss: 3.8963 - Accuracy: 0.5652 - F1: 0.5126
sub_28:Test (Best Model) - Loss: 2.5821 - Accuracy: 0.4412 - F1: 0.3940
sub_27:Test (Best Model) - Loss: 4.5941 - Accuracy: 0.3382 - F1: 0.3362
sub_22:Test (Best Model) - Loss: 2.7353 - Accuracy: 0.6471 - F1: 0.6286
sub_18:Test (Best Model) - Loss: 3.9744 - Accuracy: 0.5441 - F1: 0.5235
sub_29:Test (Best Model) - Loss: 1.9770 - Accuracy: 0.5362 - F1: 0.4777
sub_19:Test (Best Model) - Loss: 6.1485 - Accuracy: 0.4265 - F1: 0.3693
sub_23:Test (Best Model) - Loss: 3.1535 - Accuracy: 0.5507 - F1: 0.4954
sub_28:Test (Best Model) - Loss: 2.1603 - Accuracy: 0.5147 - F1: 0.4001
sub_19:Test (Best Model) - Loss: 2.4373 - Accuracy: 0.4853 - F1: 0.4456
sub_22:Test (Best Model) - Loss: 4.7633 - Accuracy: 0.4853 - F1: 0.4496
sub_26:Test (Best Model) - Loss: 2.7609 - Accuracy: 0.6176 - F1: 0.6275
sub_29:Test (Best Model) - Loss: 0.9318 - Accuracy: 0.6957 - F1: 0.6637
sub_18:Test (Best Model) - Loss: 2.7709 - Accuracy: 0.4853 - F1: 0.4583
sub_18:Test (Best Model) - Loss: 2.1346 - Accuracy: 0.5147 - F1: 0.4628
sub_28:Test (Best Model) - Loss: 4.7992 - Accuracy: 0.3676 - F1: 0.3626
sub_26:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.7059 - F1: 0.7174
sub_26:Test (Best Model) - Loss: 2.8349 - Accuracy: 0.3971 - F1: 0.4319

=== Summary Results ===

acc: 60.31 ± 6.78
F1: 57.42 ± 7.39
acc-in: 93.73 ± 3.14
F1-in: 93.53 ± 3.44
