lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.4703 - Accuracy: 0.8125 - F1: 0.8057
sub_1:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.6562 - F1: 0.6267
sub_1:Test (Best Model) - Loss: 0.6284 - Accuracy: 0.7188 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.3273 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.8964 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.3583 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.8376 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.2310 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3211 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.4133 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 1.0368 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 1.6648 - Accuracy: 0.7879 - F1: 0.7746
sub_2:Test (Best Model) - Loss: 1.8259 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 1.4621 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 1.5877 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 1.4913 - Accuracy: 0.5000 - F1: 0.4459
sub_2:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.7812 - F1: 0.7758
sub_2:Test (Best Model) - Loss: 0.7128 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.5625 - F1: 0.5466
sub_2:Test (Best Model) - Loss: 1.1573 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 1.7023 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.8206 - Accuracy: 0.6970 - F1: 0.6967
sub_2:Test (Best Model) - Loss: 0.9869 - Accuracy: 0.6970 - F1: 0.6944
sub_2:Test (Best Model) - Loss: 0.8902 - Accuracy: 0.7273 - F1: 0.7263
sub_3:Test (Best Model) - Loss: 1.4269 - Accuracy: 0.5625 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 1.2393 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 1.3128 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 1.4540 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 1.5071 - Accuracy: 0.4375 - F1: 0.4353
sub_3:Test (Best Model) - Loss: 0.9961 - Accuracy: 0.5455 - F1: 0.5455
sub_3:Test (Best Model) - Loss: 1.4240 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 1.0101 - Accuracy: 0.6061 - F1: 0.6046
sub_3:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.5758 - F1: 0.5227
sub_3:Test (Best Model) - Loss: 1.4954 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 1.9365 - Accuracy: 0.5758 - F1: 0.5722
sub_3:Test (Best Model) - Loss: 1.6434 - Accuracy: 0.5152 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 1.7002 - Accuracy: 0.4545 - F1: 0.3543
sub_3:Test (Best Model) - Loss: 2.0149 - Accuracy: 0.5455 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 2.3178 - Accuracy: 0.4242 - F1: 0.4046
sub_4:Test (Best Model) - Loss: 1.1289 - Accuracy: 0.7273 - F1: 0.7102
sub_4:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.8084 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.5213 - Accuracy: 0.8788 - F1: 0.8759
sub_4:Test (Best Model) - Loss: 1.2775 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 1.1502 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 1.0176 - Accuracy: 0.7273 - F1: 0.7102
sub_4:Test (Best Model) - Loss: 1.6206 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 2.4672 - Accuracy: 0.5758 - F1: 0.5227
sub_4:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6970 - F1: 0.6944
sub_4:Test (Best Model) - Loss: 0.8840 - Accuracy: 0.7273 - F1: 0.7179
sub_4:Test (Best Model) - Loss: 0.5415 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.4868 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.4462 - Accuracy: 0.7879 - F1: 0.7871
sub_5:Test (Best Model) - Loss: 2.0501 - Accuracy: 0.4375 - F1: 0.4375
sub_5:Test (Best Model) - Loss: 1.4776 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 2.8975 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.6250 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.9631 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.9863 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.6250 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.9153 - Accuracy: 0.6562 - F1: 0.6390
sub_5:Test (Best Model) - Loss: 0.8994 - Accuracy: 0.6562 - F1: 0.6476
sub_5:Test (Best Model) - Loss: 0.9482 - Accuracy: 0.4688 - F1: 0.4555
sub_5:Test (Best Model) - Loss: 1.1614 - Accuracy: 0.5000 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 1.5441 - Accuracy: 0.4375 - F1: 0.4000
sub_5:Test (Best Model) - Loss: 1.4181 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.6562 - F1: 0.6559
sub_6:Test (Best Model) - Loss: 1.5294 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 1.2223 - Accuracy: 0.5312 - F1: 0.5308
sub_6:Test (Best Model) - Loss: 1.1724 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 1.1325 - Accuracy: 0.6250 - F1: 0.6113
sub_6:Test (Best Model) - Loss: 0.7310 - Accuracy: 0.7812 - F1: 0.7625
sub_6:Test (Best Model) - Loss: 2.9698 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 2.5842 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 1.8482 - Accuracy: 0.5152 - F1: 0.4261
sub_6:Test (Best Model) - Loss: 2.8757 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 1.9490 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 1.1371 - Accuracy: 0.6364 - F1: 0.5696
sub_6:Test (Best Model) - Loss: 1.5537 - Accuracy: 0.5758 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 1.0777 - Accuracy: 0.6364 - F1: 0.5909
sub_6:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.7576 - F1: 0.7462
sub_6:Test (Best Model) - Loss: 1.1539 - Accuracy: 0.6364 - F1: 0.5909
sub_7:Test (Best Model) - Loss: 0.9559 - Accuracy: 0.6250 - F1: 0.5636
sub_7:Test (Best Model) - Loss: 1.6645 - Accuracy: 0.5000 - F1: 0.4182
sub_7:Test (Best Model) - Loss: 2.2827 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.9960 - Accuracy: 0.6875 - F1: 0.6667
sub_7:Test (Best Model) - Loss: 1.5230 - Accuracy: 0.5938 - F1: 0.5589
sub_7:Test (Best Model) - Loss: 1.9978 - Accuracy: 0.3125 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 1.4872 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 1.6628 - Accuracy: 0.4375 - F1: 0.4286
sub_7:Test (Best Model) - Loss: 1.8965 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.4688 - F1: 0.4555
sub_7:Test (Best Model) - Loss: 1.1373 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 1.4349 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 1.9331 - Accuracy: 0.5625 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 0.8347 - Accuracy: 0.6875 - F1: 0.6825
sub_7:Test (Best Model) - Loss: 1.1855 - Accuracy: 0.5312 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 1.7239 - Accuracy: 0.5625 - F1: 0.4909
sub_8:Test (Best Model) - Loss: 1.9829 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 1.4528 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 1.7764 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.7425 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 2.0495 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 1.0504 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 2.4771 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 1.5754 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.0595 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 1.0789 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 1.0128 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.3569 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.3807 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 1.0351 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.9800 - Accuracy: 0.7812 - F1: 0.7793
sub_9:Test (Best Model) - Loss: 1.2388 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 1.8061 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 1.8508 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 1.4307 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 2.3903 - Accuracy: 0.7812 - F1: 0.7793
sub_9:Test (Best Model) - Loss: 1.4146 - Accuracy: 0.6875 - F1: 0.6863
sub_9:Test (Best Model) - Loss: 1.5220 - Accuracy: 0.7188 - F1: 0.7163
sub_9:Test (Best Model) - Loss: 0.8603 - Accuracy: 0.8750 - F1: 0.8730
sub_10:Test (Best Model) - Loss: 1.1517 - Accuracy: 0.5625 - F1: 0.5152
sub_10:Test (Best Model) - Loss: 1.4806 - Accuracy: 0.4688 - F1: 0.4231
sub_10:Test (Best Model) - Loss: 0.9935 - Accuracy: 0.5312 - F1: 0.4684
sub_10:Test (Best Model) - Loss: 1.5861 - Accuracy: 0.5000 - F1: 0.4459
sub_10:Test (Best Model) - Loss: 1.5224 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 1.5753 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 1.4458 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 1.5276 - Accuracy: 0.5000 - F1: 0.4980
sub_10:Test (Best Model) - Loss: 2.1884 - Accuracy: 0.3750 - F1: 0.3750
sub_10:Test (Best Model) - Loss: 1.6991 - Accuracy: 0.5758 - F1: 0.5558
sub_10:Test (Best Model) - Loss: 1.7372 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 1.1504 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 1.2716 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 1.6215 - Accuracy: 0.5758 - F1: 0.5754
sub_11:Test (Best Model) - Loss: 3.1241 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 2.2144 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 2.3761 - Accuracy: 0.3939 - F1: 0.3889
sub_11:Test (Best Model) - Loss: 1.7815 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 2.8835 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 1.7439 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 1.6361 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.6667 - F1: 0.5935
sub_11:Test (Best Model) - Loss: 2.0285 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 1.6950 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 1.0533 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 1.2536 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 1.5411 - Accuracy: 0.6364 - F1: 0.5696
sub_11:Test (Best Model) - Loss: 1.0023 - Accuracy: 0.6667 - F1: 0.6459
sub_11:Test (Best Model) - Loss: 1.6498 - Accuracy: 0.5758 - F1: 0.4653
sub_12:Test (Best Model) - Loss: 0.9258 - Accuracy: 0.7500 - F1: 0.7229
sub_12:Test (Best Model) - Loss: 0.5682 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.9789 - Accuracy: 0.6875 - F1: 0.6135
sub_12:Test (Best Model) - Loss: 1.4171 - Accuracy: 0.6562 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 1.0868 - Accuracy: 0.6970 - F1: 0.6591
sub_12:Test (Best Model) - Loss: 0.9637 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 0.8754 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.9607 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 1.4867 - Accuracy: 0.6364 - F1: 0.5417
sub_12:Test (Best Model) - Loss: 1.1234 - Accuracy: 0.6875 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.6875 - F1: 0.6761
sub_12:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.6562 - F1: 0.6559
sub_12:Test (Best Model) - Loss: 1.4772 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 1.1788 - Accuracy: 0.6875 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 0.2877 - Accuracy: 0.8438 - F1: 0.8398
sub_13:Test (Best Model) - Loss: 0.8599 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.2199 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.4863 - Accuracy: 0.8750 - F1: 0.8730
sub_13:Test (Best Model) - Loss: 0.2481 - Accuracy: 0.9062 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.4618 - Accuracy: 0.7576 - F1: 0.7462
sub_13:Test (Best Model) - Loss: 0.6014 - Accuracy: 0.7576 - F1: 0.7462
sub_13:Test (Best Model) - Loss: 0.5375 - Accuracy: 0.8182 - F1: 0.8167
sub_13:Test (Best Model) - Loss: 0.7261 - Accuracy: 0.7576 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.6970 - F1: 0.6591
sub_13:Test (Best Model) - Loss: 0.7441 - Accuracy: 0.8750 - F1: 0.8750
sub_13:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.7500 - F1: 0.7409
sub_13:Test (Best Model) - Loss: 0.5117 - Accuracy: 0.8125 - F1: 0.8125
sub_13:Test (Best Model) - Loss: 0.7493 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.7812 - F1: 0.7810
sub_14:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 1.0267 - Accuracy: 0.6562 - F1: 0.5883
sub_14:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.7812 - F1: 0.7793
sub_14:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.3848 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.7665 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.5458 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.5938 - F1: 0.4793
sub_14:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.7188 - F1: 0.6632
sub_14:Test (Best Model) - Loss: 0.8111 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 1.2496 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.6562 - F1: 0.5594
sub_14:Test (Best Model) - Loss: 1.1319 - Accuracy: 0.7500 - F1: 0.7091
sub_15:Test (Best Model) - Loss: 2.0889 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.6250 - F1: 0.6250
sub_15:Test (Best Model) - Loss: 1.2473 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 1.3618 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 1.1827 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 1.6419 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 2.7635 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 1.8049 - Accuracy: 0.5938 - F1: 0.5733
sub_15:Test (Best Model) - Loss: 2.6769 - Accuracy: 0.4688 - F1: 0.4682
sub_15:Test (Best Model) - Loss: 1.4792 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 1.3274 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 2.2390 - Accuracy: 0.4062 - F1: 0.3267
sub_15:Test (Best Model) - Loss: 1.2323 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 1.5591 - Accuracy: 0.4375 - F1: 0.4375
sub_16:Test (Best Model) - Loss: 1.0994 - Accuracy: 0.6562 - F1: 0.6559
sub_16:Test (Best Model) - Loss: 1.0585 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 1.2861 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 1.1474 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 1.6685 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 1.2081 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 1.5279 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 1.2251 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 2.2013 - Accuracy: 0.6562 - F1: 0.6559
sub_16:Test (Best Model) - Loss: 1.9366 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 1.8989 - Accuracy: 0.5938 - F1: 0.5135
sub_16:Test (Best Model) - Loss: 1.9114 - Accuracy: 0.5625 - F1: 0.4909
sub_16:Test (Best Model) - Loss: 1.4929 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 1.4616 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 1.2686 - Accuracy: 0.6364 - F1: 0.6071
sub_17:Test (Best Model) - Loss: 0.9713 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 1.3140 - Accuracy: 0.5455 - F1: 0.5299
sub_17:Test (Best Model) - Loss: 1.7184 - Accuracy: 0.6061 - F1: 0.4850
sub_17:Test (Best Model) - Loss: 0.7995 - Accuracy: 0.6061 - F1: 0.5815
sub_17:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.5152 - F1: 0.4923
sub_17:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 2.4500 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 1.2829 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 1.3010 - Accuracy: 0.4545 - F1: 0.4107
sub_17:Test (Best Model) - Loss: 0.8949 - Accuracy: 0.5938 - F1: 0.5733
sub_17:Test (Best Model) - Loss: 1.6134 - Accuracy: 0.6250 - F1: 0.6000
sub_17:Test (Best Model) - Loss: 2.0667 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 1.5559 - Accuracy: 0.6250 - F1: 0.6190
sub_17:Test (Best Model) - Loss: 1.5054 - Accuracy: 0.5625 - F1: 0.5466
sub_18:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.7576 - F1: 0.7556
sub_18:Test (Best Model) - Loss: 0.6170 - Accuracy: 0.7879 - F1: 0.7806
sub_18:Test (Best Model) - Loss: 0.4553 - Accuracy: 0.7879 - F1: 0.7806
sub_18:Test (Best Model) - Loss: 0.8751 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.7480 - Accuracy: 0.7500 - F1: 0.7500
sub_18:Test (Best Model) - Loss: 0.7655 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 1.2470 - Accuracy: 0.6562 - F1: 0.6476
sub_18:Test (Best Model) - Loss: 0.7133 - Accuracy: 0.8438 - F1: 0.8359
sub_18:Test (Best Model) - Loss: 0.8430 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.7500 - F1: 0.7333
sub_19:Test (Best Model) - Loss: 2.4535 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 1.8108 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 1.2926 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 3.0812 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 2.0180 - Accuracy: 0.5312 - F1: 0.3469
sub_19:Test (Best Model) - Loss: 1.7700 - Accuracy: 0.5312 - F1: 0.4684
sub_19:Test (Best Model) - Loss: 1.4380 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 1.4223 - Accuracy: 0.4375 - F1: 0.3766
sub_19:Test (Best Model) - Loss: 1.8082 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 1.5255 - Accuracy: 0.4688 - F1: 0.4555
sub_19:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.6875 - F1: 0.6875
sub_19:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 0.9101 - Accuracy: 0.6562 - F1: 0.6390
sub_19:Test (Best Model) - Loss: 0.7836 - Accuracy: 0.6875 - F1: 0.6825
sub_19:Test (Best Model) - Loss: 0.7859 - Accuracy: 0.6875 - F1: 0.6825
sub_20:Test (Best Model) - Loss: 1.4071 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 1.0950 - Accuracy: 0.6562 - F1: 0.6102
sub_20:Test (Best Model) - Loss: 1.7191 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.6562 - F1: 0.5883
sub_20:Test (Best Model) - Loss: 2.3230 - Accuracy: 0.5312 - F1: 0.4684
sub_20:Test (Best Model) - Loss: 1.4493 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 1.9832 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 1.8672 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 1.8713 - Accuracy: 0.7188 - F1: 0.6811
sub_20:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 2.1812 - Accuracy: 0.5455 - F1: 0.5299
sub_20:Test (Best Model) - Loss: 2.4496 - Accuracy: 0.5758 - F1: 0.5227
sub_20:Test (Best Model) - Loss: 2.0370 - Accuracy: 0.5455 - F1: 0.5171
sub_20:Test (Best Model) - Loss: 3.1613 - Accuracy: 0.5455 - F1: 0.5299
sub_20:Test (Best Model) - Loss: 2.0601 - Accuracy: 0.7273 - F1: 0.7102
sub_21:Test (Best Model) - Loss: 2.3739 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 1.9987 - Accuracy: 0.3750 - F1: 0.3522
sub_21:Test (Best Model) - Loss: 2.8064 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 2.2710 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 2.0081 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 1.5367 - Accuracy: 0.5625 - F1: 0.4167
sub_21:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 1.9222 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 1.6338 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 1.8044 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 1.9013 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 2.3144 - Accuracy: 0.3750 - F1: 0.3522
sub_21:Test (Best Model) - Loss: 2.3654 - Accuracy: 0.3125 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 2.2757 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 2.0949 - Accuracy: 0.4062 - F1: 0.3764
sub_22:Test (Best Model) - Loss: 1.1182 - Accuracy: 0.5938 - F1: 0.5733
sub_22:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.6562 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.9616 - Accuracy: 0.6250 - F1: 0.5636
sub_22:Test (Best Model) - Loss: 1.0534 - Accuracy: 0.7812 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 1.6844 - Accuracy: 0.5758 - F1: 0.4225
sub_22:Test (Best Model) - Loss: 1.1221 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.9617 - Accuracy: 0.7879 - F1: 0.7664
sub_22:Test (Best Model) - Loss: 1.6326 - Accuracy: 0.5758 - F1: 0.4225
sub_22:Test (Best Model) - Loss: 1.4738 - Accuracy: 0.6061 - F1: 0.5460
sub_22:Test (Best Model) - Loss: 1.1105 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 1.0723 - Accuracy: 0.6562 - F1: 0.6532
sub_22:Test (Best Model) - Loss: 0.8752 - Accuracy: 0.7500 - F1: 0.7333
sub_22:Test (Best Model) - Loss: 1.0477 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.8891 - Accuracy: 0.6875 - F1: 0.6761
sub_23:Test (Best Model) - Loss: 0.9912 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 1.0686 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 1.0404 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.6364 - F1: 0.5417
sub_23:Test (Best Model) - Loss: 0.9982 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.5625 - F1: 0.5625
sub_23:Test (Best Model) - Loss: 0.8964 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.4386 - Accuracy: 0.8125 - F1: 0.8000
sub_23:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 1.5008 - Accuracy: 0.6364 - F1: 0.5909
sub_23:Test (Best Model) - Loss: 0.7525 - Accuracy: 0.6970 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 1.2722 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 1.9264 - Accuracy: 0.6364 - F1: 0.5696
sub_24:Test (Best Model) - Loss: 1.0633 - Accuracy: 0.5000 - F1: 0.4459
sub_24:Test (Best Model) - Loss: 1.5381 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 1.4356 - Accuracy: 0.5312 - F1: 0.5077
sub_24:Test (Best Model) - Loss: 1.0962 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 1.3066 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 1.1499 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 1.2179 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.8234 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.8960 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 1.7713 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 1.7635 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 1.7528 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 1.9852 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 1.8560 - Accuracy: 0.5312 - F1: 0.5077
sub_25:Test (Best Model) - Loss: 2.0558 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 2.0404 - Accuracy: 0.5152 - F1: 0.5111
sub_25:Test (Best Model) - Loss: 1.9644 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 1.9325 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 2.0026 - Accuracy: 0.4545 - F1: 0.4107
sub_25:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.5625 - F1: 0.4909
sub_25:Test (Best Model) - Loss: 0.8356 - Accuracy: 0.5938 - F1: 0.5393
sub_25:Test (Best Model) - Loss: 1.0737 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 1.5457 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 1.0901 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 1.0184 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 1.2799 - Accuracy: 0.7188 - F1: 0.6632
sub_25:Test (Best Model) - Loss: 1.1217 - Accuracy: 0.6875 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 1.5556 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 1.8120 - Accuracy: 0.5938 - F1: 0.5393
sub_26:Test (Best Model) - Loss: 1.2643 - Accuracy: 0.6667 - F1: 0.6553
sub_26:Test (Best Model) - Loss: 1.9876 - Accuracy: 0.6970 - F1: 0.6726
sub_26:Test (Best Model) - Loss: 0.9768 - Accuracy: 0.7273 - F1: 0.7179
sub_26:Test (Best Model) - Loss: 0.9295 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.9651 - Accuracy: 0.7273 - F1: 0.6857
sub_26:Test (Best Model) - Loss: 0.8318 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 1.1201 - Accuracy: 0.6250 - F1: 0.6190
sub_26:Test (Best Model) - Loss: 0.9736 - Accuracy: 0.7812 - F1: 0.7810
sub_26:Test (Best Model) - Loss: 1.0410 - Accuracy: 0.6875 - F1: 0.6537
sub_26:Test (Best Model) - Loss: 0.8884 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.5315 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.9189 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.5191 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.5411 - Accuracy: 0.8438 - F1: 0.8303
sub_27:Test (Best Model) - Loss: 1.2686 - Accuracy: 0.6364 - F1: 0.6071
sub_27:Test (Best Model) - Loss: 0.9713 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 1.3140 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 1.7184 - Accuracy: 0.6061 - F1: 0.4850
sub_27:Test (Best Model) - Loss: 0.7995 - Accuracy: 0.6061 - F1: 0.5815
sub_27:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.5152 - F1: 0.4923
sub_27:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 2.4500 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 1.2829 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 1.3010 - Accuracy: 0.4545 - F1: 0.4107
sub_27:Test (Best Model) - Loss: 0.8949 - Accuracy: 0.5938 - F1: 0.5733
sub_27:Test (Best Model) - Loss: 1.6134 - Accuracy: 0.6250 - F1: 0.6000
sub_27:Test (Best Model) - Loss: 2.0667 - Accuracy: 0.5625 - F1: 0.5333
sub_27:Test (Best Model) - Loss: 1.5559 - Accuracy: 0.6250 - F1: 0.6190
sub_27:Test (Best Model) - Loss: 1.5054 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.7496 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 1.1462 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 2.2437 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 2.4581 - Accuracy: 0.3125 - F1: 0.3016
sub_28:Test (Best Model) - Loss: 3.6466 - Accuracy: 0.4688 - F1: 0.4555
sub_28:Test (Best Model) - Loss: 2.6911 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 3.4162 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 2.2226 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 5.5043 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 1.7619 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 1.6937 - Accuracy: 0.3125 - F1: 0.3098
sub_28:Test (Best Model) - Loss: 1.5821 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 1.6655 - Accuracy: 0.6875 - F1: 0.6863
sub_28:Test (Best Model) - Loss: 1.7133 - Accuracy: 0.3750 - F1: 0.2727
sub_29:Test (Best Model) - Loss: 1.4532 - Accuracy: 0.7188 - F1: 0.6632
sub_29:Test (Best Model) - Loss: 1.1101 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 1.6980 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.9608 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.1659 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.1745 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.0923 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2384 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.1159 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.3613 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2939 - Accuracy: 0.8788 - F1: 0.8759
sub_29:Test (Best Model) - Loss: 0.0641 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.0327 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1279 - Accuracy: 0.9394 - F1: 0.9389

=== Summary Results ===

acc: 64.27 ± 10.75
F1: 61.55 ± 11.48
acc-in: 71.81 ± 8.61
F1-in: 69.24 ± 9.13
