lr: 0.0001
sub_22:Test (Best Model) - Loss: 1.3361 - Accuracy: 0.3824 - F1: 0.3766
sub_20:Test (Best Model) - Loss: 1.2496 - Accuracy: 0.5000 - F1: 0.4871
sub_6:Test (Best Model) - Loss: 1.2991 - Accuracy: 0.3971 - F1: 0.3913
sub_7:Test (Best Model) - Loss: 1.2694 - Accuracy: 0.4412 - F1: 0.4379
sub_25:Test (Best Model) - Loss: 1.2121 - Accuracy: 0.6232 - F1: 0.6042
sub_18:Test (Best Model) - Loss: 1.1501 - Accuracy: 0.7536 - F1: 0.7604
sub_8:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.4265 - F1: 0.4124
sub_19:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.2500 - F1: 0.2541
sub_21:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.4706 - F1: 0.4609
sub_15:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.6176 - F1: 0.6228
sub_2:Test (Best Model) - Loss: 1.2443 - Accuracy: 0.5362 - F1: 0.5456
sub_26:Test (Best Model) - Loss: 1.2489 - Accuracy: 0.5362 - F1: 0.5114
sub_14:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.3382 - F1: 0.2598
sub_16:Test (Best Model) - Loss: 1.2466 - Accuracy: 0.5735 - F1: 0.5625
sub_17:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.5072 - F1: 0.4854
sub_29:Test (Best Model) - Loss: 1.2362 - Accuracy: 0.5147 - F1: 0.5393
sub_1:Test (Best Model) - Loss: 1.2062 - Accuracy: 0.5294 - F1: 0.5526
sub_13:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.5588 - F1: 0.5802
sub_12:Test (Best Model) - Loss: 1.1630 - Accuracy: 0.5735 - F1: 0.5842
sub_4:Test (Best Model) - Loss: 1.2153 - Accuracy: 0.5072 - F1: 0.5236
sub_23:Test (Best Model) - Loss: 1.2311 - Accuracy: 0.5072 - F1: 0.5065
sub_5:Test (Best Model) - Loss: 1.2713 - Accuracy: 0.6471 - F1: 0.5944
sub_22:Test (Best Model) - Loss: 1.3245 - Accuracy: 0.3529 - F1: 0.3340
sub_3:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.5000 - F1: 0.5313
sub_28:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.5441 - F1: 0.4873
sub_24:Test (Best Model) - Loss: 1.1655 - Accuracy: 0.5735 - F1: 0.5502
sub_10:Test (Best Model) - Loss: 1.1765 - Accuracy: 0.5735 - F1: 0.5458
sub_11:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.5362 - F1: 0.4847
sub_27:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.5072 - F1: 0.4854
sub_7:Test (Best Model) - Loss: 1.2218 - Accuracy: 0.5441 - F1: 0.5418
sub_18:Test (Best Model) - Loss: 1.1821 - Accuracy: 0.6522 - F1: 0.6570
sub_20:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.5294 - F1: 0.5176
sub_6:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.4118 - F1: 0.4147
sub_15:Test (Best Model) - Loss: 1.2759 - Accuracy: 0.5588 - F1: 0.5687
sub_8:Test (Best Model) - Loss: 1.3066 - Accuracy: 0.4412 - F1: 0.4333
sub_19:Test (Best Model) - Loss: 1.3937 - Accuracy: 0.2794 - F1: 0.2114
sub_2:Test (Best Model) - Loss: 1.2470 - Accuracy: 0.5507 - F1: 0.5268
sub_26:Test (Best Model) - Loss: 1.2175 - Accuracy: 0.6377 - F1: 0.6035
sub_9:Test (Best Model) - Loss: 1.0880 - Accuracy: 0.5882 - F1: 0.5492
sub_21:Test (Best Model) - Loss: 1.2403 - Accuracy: 0.4706 - F1: 0.4527
sub_14:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.3529 - F1: 0.2698
sub_25:Test (Best Model) - Loss: 1.1410 - Accuracy: 0.6812 - F1: 0.6790
sub_23:Test (Best Model) - Loss: 1.1908 - Accuracy: 0.6377 - F1: 0.6518
sub_1:Test (Best Model) - Loss: 1.2089 - Accuracy: 0.5882 - F1: 0.5844
sub_13:Test (Best Model) - Loss: 1.2925 - Accuracy: 0.3382 - F1: 0.3476
sub_22:Test (Best Model) - Loss: 1.2831 - Accuracy: 0.4412 - F1: 0.4579
sub_3:Test (Best Model) - Loss: 1.2129 - Accuracy: 0.5735 - F1: 0.5920
sub_17:Test (Best Model) - Loss: 1.2411 - Accuracy: 0.5072 - F1: 0.4854
sub_18:Test (Best Model) - Loss: 1.1814 - Accuracy: 0.7536 - F1: 0.7552
sub_12:Test (Best Model) - Loss: 1.2202 - Accuracy: 0.5294 - F1: 0.5028
sub_4:Test (Best Model) - Loss: 1.2406 - Accuracy: 0.4203 - F1: 0.4265
sub_28:Test (Best Model) - Loss: 1.3504 - Accuracy: 0.3529 - F1: 0.3364
sub_11:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.5217 - F1: 0.4981
sub_5:Test (Best Model) - Loss: 1.2507 - Accuracy: 0.5147 - F1: 0.4621
sub_29:Test (Best Model) - Loss: 1.1394 - Accuracy: 0.6471 - F1: 0.6491
sub_16:Test (Best Model) - Loss: 1.2130 - Accuracy: 0.5882 - F1: 0.5573
sub_10:Test (Best Model) - Loss: 1.2053 - Accuracy: 0.7059 - F1: 0.7204
sub_27:Test (Best Model) - Loss: 1.2411 - Accuracy: 0.5072 - F1: 0.4854
sub_6:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.3676 - F1: 0.3679
sub_26:Test (Best Model) - Loss: 1.1821 - Accuracy: 0.5652 - F1: 0.5336
sub_7:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.6029 - F1: 0.5922
sub_2:Test (Best Model) - Loss: 1.2350 - Accuracy: 0.5942 - F1: 0.5656
sub_20:Test (Best Model) - Loss: 1.2277 - Accuracy: 0.5588 - F1: 0.5631
sub_9:Test (Best Model) - Loss: 1.1767 - Accuracy: 0.6618 - F1: 0.6068
sub_19:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.3382 - F1: 0.2997
sub_14:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.2794 - F1: 0.2187
sub_24:Test (Best Model) - Loss: 1.1331 - Accuracy: 0.6324 - F1: 0.5988
sub_25:Test (Best Model) - Loss: 1.2372 - Accuracy: 0.5362 - F1: 0.5342
sub_23:Test (Best Model) - Loss: 1.1822 - Accuracy: 0.6522 - F1: 0.6591
sub_15:Test (Best Model) - Loss: 1.2123 - Accuracy: 0.6176 - F1: 0.6234
sub_18:Test (Best Model) - Loss: 1.2059 - Accuracy: 0.6377 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.5000 - F1: 0.5251
sub_4:Test (Best Model) - Loss: 1.2508 - Accuracy: 0.4638 - F1: 0.4827
sub_8:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.5000 - F1: 0.4888
sub_12:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.5882 - F1: 0.5952
sub_21:Test (Best Model) - Loss: 1.2699 - Accuracy: 0.4706 - F1: 0.4595
sub_11:Test (Best Model) - Loss: 1.2963 - Accuracy: 0.4928 - F1: 0.4624
sub_1:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.5000 - F1: 0.5162
sub_29:Test (Best Model) - Loss: 1.2103 - Accuracy: 0.6324 - F1: 0.6535
sub_5:Test (Best Model) - Loss: 1.2501 - Accuracy: 0.6176 - F1: 0.5706
sub_13:Test (Best Model) - Loss: 1.2904 - Accuracy: 0.5000 - F1: 0.5010
sub_20:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.4559 - F1: 0.4439
sub_17:Test (Best Model) - Loss: 1.2589 - Accuracy: 0.4348 - F1: 0.4229
sub_22:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.4706 - F1: 0.4435
sub_10:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.5294 - F1: 0.5208
sub_9:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.7353 - F1: 0.6971
sub_6:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.3529 - F1: 0.3528
sub_19:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3235 - F1: 0.3202
sub_16:Test (Best Model) - Loss: 1.1990 - Accuracy: 0.6029 - F1: 0.6024
sub_28:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.4412 - F1: 0.3771
sub_18:Test (Best Model) - Loss: 1.1633 - Accuracy: 0.6667 - F1: 0.6833
sub_27:Test (Best Model) - Loss: 1.2589 - Accuracy: 0.4348 - F1: 0.4229
sub_26:Test (Best Model) - Loss: 1.1770 - Accuracy: 0.6377 - F1: 0.6112
sub_21:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.4559 - F1: 0.4227
sub_3:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.5588 - F1: 0.5488
sub_25:Test (Best Model) - Loss: 1.2209 - Accuracy: 0.5362 - F1: 0.4836
sub_15:Test (Best Model) - Loss: 1.2722 - Accuracy: 0.5000 - F1: 0.5278
sub_8:Test (Best Model) - Loss: 1.3422 - Accuracy: 0.4412 - F1: 0.4360
sub_20:Test (Best Model) - Loss: 1.2498 - Accuracy: 0.5147 - F1: 0.4854
sub_14:Test (Best Model) - Loss: 1.3716 - Accuracy: 0.3971 - F1: 0.3014
sub_5:Test (Best Model) - Loss: 1.3208 - Accuracy: 0.5294 - F1: 0.4908
sub_23:Test (Best Model) - Loss: 1.1907 - Accuracy: 0.6522 - F1: 0.6673
sub_13:Test (Best Model) - Loss: 1.2691 - Accuracy: 0.5000 - F1: 0.4635
sub_4:Test (Best Model) - Loss: 1.2709 - Accuracy: 0.4348 - F1: 0.4325
sub_7:Test (Best Model) - Loss: 1.2273 - Accuracy: 0.5735 - F1: 0.5431
sub_1:Test (Best Model) - Loss: 1.2687 - Accuracy: 0.5147 - F1: 0.5238
sub_22:Test (Best Model) - Loss: 1.2782 - Accuracy: 0.4265 - F1: 0.4250
sub_11:Test (Best Model) - Loss: 1.2476 - Accuracy: 0.5362 - F1: 0.5312
sub_2:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.5217 - F1: 0.5212
sub_24:Test (Best Model) - Loss: 1.1781 - Accuracy: 0.5441 - F1: 0.5067
sub_15:Test (Best Model) - Loss: 1.3057 - Accuracy: 0.4853 - F1: 0.5044
sub_6:Test (Best Model) - Loss: 1.3358 - Accuracy: 0.4265 - F1: 0.4035
sub_29:Test (Best Model) - Loss: 1.1584 - Accuracy: 0.6765 - F1: 0.6356
sub_9:Test (Best Model) - Loss: 1.2266 - Accuracy: 0.5882 - F1: 0.5725
sub_19:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2794 - F1: 0.2162
sub_12:Test (Best Model) - Loss: 1.2769 - Accuracy: 0.5000 - F1: 0.4955
sub_17:Test (Best Model) - Loss: 1.2869 - Accuracy: 0.4783 - F1: 0.4848
sub_14:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1843
sub_7:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.4118 - F1: 0.4250
sub_16:Test (Best Model) - Loss: 1.2593 - Accuracy: 0.4853 - F1: 0.4677
sub_10:Test (Best Model) - Loss: 1.2429 - Accuracy: 0.5147 - F1: 0.5089
sub_3:Test (Best Model) - Loss: 1.1929 - Accuracy: 0.6176 - F1: 0.6158
sub_20:Test (Best Model) - Loss: 1.2502 - Accuracy: 0.5588 - F1: 0.5222
sub_21:Test (Best Model) - Loss: 1.2565 - Accuracy: 0.4265 - F1: 0.4016
sub_13:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.4118 - F1: 0.3849
sub_18:Test (Best Model) - Loss: 1.1708 - Accuracy: 0.6176 - F1: 0.5882
sub_28:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.4118 - F1: 0.3628
sub_5:Test (Best Model) - Loss: 1.2805 - Accuracy: 0.5735 - F1: 0.5234
sub_4:Test (Best Model) - Loss: 1.2295 - Accuracy: 0.4493 - F1: 0.4555
sub_27:Test (Best Model) - Loss: 1.2869 - Accuracy: 0.4783 - F1: 0.4848
sub_2:Test (Best Model) - Loss: 1.2349 - Accuracy: 0.5507 - F1: 0.5637
sub_26:Test (Best Model) - Loss: 1.1155 - Accuracy: 0.6087 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 1.3518 - Accuracy: 0.4559 - F1: 0.4284
sub_19:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.5147 - F1: 0.4452
sub_25:Test (Best Model) - Loss: 1.2305 - Accuracy: 0.6087 - F1: 0.5784
sub_11:Test (Best Model) - Loss: 1.2274 - Accuracy: 0.6377 - F1: 0.6350
sub_23:Test (Best Model) - Loss: 1.1182 - Accuracy: 0.6377 - F1: 0.6633
sub_6:Test (Best Model) - Loss: 1.2759 - Accuracy: 0.4783 - F1: 0.4663
sub_1:Test (Best Model) - Loss: 1.1987 - Accuracy: 0.5735 - F1: 0.5943
sub_28:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.3971 - F1: 0.3725
sub_22:Test (Best Model) - Loss: 1.1694 - Accuracy: 0.5362 - F1: 0.5119
sub_10:Test (Best Model) - Loss: 1.2399 - Accuracy: 0.5000 - F1: 0.5153
sub_20:Test (Best Model) - Loss: 1.2028 - Accuracy: 0.5294 - F1: 0.4952
sub_14:Test (Best Model) - Loss: 1.1642 - Accuracy: 0.5588 - F1: 0.5931
sub_29:Test (Best Model) - Loss: 1.1547 - Accuracy: 0.5882 - F1: 0.5903
sub_4:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.6522 - F1: 0.6419
sub_15:Test (Best Model) - Loss: 1.1413 - Accuracy: 0.5735 - F1: 0.5886
sub_9:Test (Best Model) - Loss: 1.1749 - Accuracy: 0.6618 - F1: 0.6325
sub_7:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.5588 - F1: 0.5213
sub_18:Test (Best Model) - Loss: 1.1927 - Accuracy: 0.5588 - F1: 0.5756
sub_8:Test (Best Model) - Loss: 1.2949 - Accuracy: 0.4706 - F1: 0.4445
sub_12:Test (Best Model) - Loss: 1.1702 - Accuracy: 0.6176 - F1: 0.6127
sub_24:Test (Best Model) - Loss: 1.2637 - Accuracy: 0.6029 - F1: 0.5782
sub_13:Test (Best Model) - Loss: 1.2677 - Accuracy: 0.4638 - F1: 0.3869
sub_17:Test (Best Model) - Loss: 1.1818 - Accuracy: 0.5942 - F1: 0.5935
sub_16:Test (Best Model) - Loss: 1.1767 - Accuracy: 0.6176 - F1: 0.5971
sub_2:Test (Best Model) - Loss: 1.1776 - Accuracy: 0.5588 - F1: 0.5587
sub_3:Test (Best Model) - Loss: 1.1126 - Accuracy: 0.7101 - F1: 0.6841
sub_26:Test (Best Model) - Loss: 1.1974 - Accuracy: 0.5441 - F1: 0.5079
sub_6:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.4638 - F1: 0.4188
sub_27:Test (Best Model) - Loss: 1.1818 - Accuracy: 0.5942 - F1: 0.5935
sub_21:Test (Best Model) - Loss: 1.0809 - Accuracy: 0.6618 - F1: 0.6586
sub_22:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.4348 - F1: 0.3417
sub_19:Test (Best Model) - Loss: 1.1598 - Accuracy: 0.7206 - F1: 0.7152
sub_25:Test (Best Model) - Loss: 1.2246 - Accuracy: 0.5735 - F1: 0.5535
sub_11:Test (Best Model) - Loss: 1.2284 - Accuracy: 0.5072 - F1: 0.4384
sub_5:Test (Best Model) - Loss: 1.1381 - Accuracy: 0.5882 - F1: 0.5713
sub_28:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.3529 - F1: 0.2700
sub_4:Test (Best Model) - Loss: 1.1730 - Accuracy: 0.6377 - F1: 0.6224
sub_24:Test (Best Model) - Loss: 1.2482 - Accuracy: 0.6324 - F1: 0.6087
sub_14:Test (Best Model) - Loss: 1.2095 - Accuracy: 0.5000 - F1: 0.5272
sub_10:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.5441 - F1: 0.5491
sub_12:Test (Best Model) - Loss: 1.1831 - Accuracy: 0.6667 - F1: 0.6516
sub_7:Test (Best Model) - Loss: 1.2799 - Accuracy: 0.5147 - F1: 0.4545
sub_1:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.6377 - F1: 0.6324
sub_18:Test (Best Model) - Loss: 1.2028 - Accuracy: 0.5882 - F1: 0.5687
sub_20:Test (Best Model) - Loss: 1.2259 - Accuracy: 0.4706 - F1: 0.4514
sub_2:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.4118 - F1: 0.3761
sub_9:Test (Best Model) - Loss: 1.0743 - Accuracy: 0.6029 - F1: 0.5687
sub_17:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3768 - F1: 0.3559
sub_15:Test (Best Model) - Loss: 1.2176 - Accuracy: 0.5588 - F1: 0.5743
sub_28:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.3088 - F1: 0.1987
sub_29:Test (Best Model) - Loss: 1.1066 - Accuracy: 0.6912 - F1: 0.6761
sub_26:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.5882 - F1: 0.5270
sub_23:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.3529 - F1: 0.2798
sub_16:Test (Best Model) - Loss: 1.1829 - Accuracy: 0.6029 - F1: 0.5811
sub_8:Test (Best Model) - Loss: 1.2563 - Accuracy: 0.4559 - F1: 0.4173
sub_27:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3768 - F1: 0.3559
sub_19:Test (Best Model) - Loss: 1.1915 - Accuracy: 0.5735 - F1: 0.5512
sub_3:Test (Best Model) - Loss: 1.2465 - Accuracy: 0.4928 - F1: 0.4658
sub_4:Test (Best Model) - Loss: 1.1491 - Accuracy: 0.6377 - F1: 0.6321
sub_11:Test (Best Model) - Loss: 1.1898 - Accuracy: 0.5362 - F1: 0.4909
sub_13:Test (Best Model) - Loss: 1.2782 - Accuracy: 0.4493 - F1: 0.3909
sub_25:Test (Best Model) - Loss: 1.2608 - Accuracy: 0.4118 - F1: 0.3906
sub_6:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.5217 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 1.1375 - Accuracy: 0.5882 - F1: 0.5709
sub_22:Test (Best Model) - Loss: 1.2413 - Accuracy: 0.4783 - F1: 0.4325
sub_18:Test (Best Model) - Loss: 1.2111 - Accuracy: 0.6029 - F1: 0.6223
sub_20:Test (Best Model) - Loss: 1.2500 - Accuracy: 0.4853 - F1: 0.4591
sub_2:Test (Best Model) - Loss: 1.2713 - Accuracy: 0.4853 - F1: 0.4787
sub_24:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.5588 - F1: 0.5292
sub_5:Test (Best Model) - Loss: 1.2225 - Accuracy: 0.5441 - F1: 0.5295
sub_9:Test (Best Model) - Loss: 1.1718 - Accuracy: 0.4559 - F1: 0.3650
sub_12:Test (Best Model) - Loss: 1.2132 - Accuracy: 0.6377 - F1: 0.6407
sub_10:Test (Best Model) - Loss: 1.1926 - Accuracy: 0.6765 - F1: 0.6641
sub_1:Test (Best Model) - Loss: 1.2199 - Accuracy: 0.6812 - F1: 0.6769
sub_15:Test (Best Model) - Loss: 1.3136 - Accuracy: 0.4118 - F1: 0.4275
sub_29:Test (Best Model) - Loss: 1.1782 - Accuracy: 0.5441 - F1: 0.5464
sub_17:Test (Best Model) - Loss: 1.3306 - Accuracy: 0.3768 - F1: 0.3757
sub_23:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.3088 - F1: 0.2283
sub_14:Test (Best Model) - Loss: 1.1720 - Accuracy: 0.5735 - F1: 0.5625
sub_11:Test (Best Model) - Loss: 1.2634 - Accuracy: 0.5362 - F1: 0.4885
sub_16:Test (Best Model) - Loss: 1.3053 - Accuracy: 0.5441 - F1: 0.5280
sub_8:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.4265 - F1: 0.4091
sub_4:Test (Best Model) - Loss: 1.2670 - Accuracy: 0.5217 - F1: 0.5281
sub_26:Test (Best Model) - Loss: 1.2440 - Accuracy: 0.5588 - F1: 0.5567
sub_7:Test (Best Model) - Loss: 1.2974 - Accuracy: 0.5294 - F1: 0.5019
sub_19:Test (Best Model) - Loss: 1.2134 - Accuracy: 0.6618 - F1: 0.6422
sub_25:Test (Best Model) - Loss: 1.2961 - Accuracy: 0.4412 - F1: 0.3987
sub_27:Test (Best Model) - Loss: 1.3306 - Accuracy: 0.3768 - F1: 0.3757
sub_28:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.2941 - F1: 0.1779
sub_22:Test (Best Model) - Loss: 1.2854 - Accuracy: 0.4348 - F1: 0.3653
sub_1:Test (Best Model) - Loss: 1.3040 - Accuracy: 0.4928 - F1: 0.4945
sub_21:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.5882 - F1: 0.5138
sub_18:Test (Best Model) - Loss: 1.2150 - Accuracy: 0.4706 - F1: 0.4942
sub_6:Test (Best Model) - Loss: 1.2234 - Accuracy: 0.5507 - F1: 0.5167
sub_10:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.6176 - F1: 0.5406
sub_5:Test (Best Model) - Loss: 1.1939 - Accuracy: 0.6324 - F1: 0.6428
sub_13:Test (Best Model) - Loss: 1.2591 - Accuracy: 0.5652 - F1: 0.5563
sub_20:Test (Best Model) - Loss: 1.2643 - Accuracy: 0.4118 - F1: 0.3818
sub_26:Test (Best Model) - Loss: 1.2677 - Accuracy: 0.5000 - F1: 0.4854
sub_2:Test (Best Model) - Loss: 1.2247 - Accuracy: 0.5735 - F1: 0.5473
sub_9:Test (Best Model) - Loss: 1.1425 - Accuracy: 0.6765 - F1: 0.6455
sub_3:Test (Best Model) - Loss: 1.1856 - Accuracy: 0.5362 - F1: 0.5149
sub_23:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.4559 - F1: 0.3983
sub_24:Test (Best Model) - Loss: 1.2222 - Accuracy: 0.5000 - F1: 0.4715
sub_25:Test (Best Model) - Loss: 1.3034 - Accuracy: 0.4706 - F1: 0.4599
sub_7:Test (Best Model) - Loss: 1.3005 - Accuracy: 0.4559 - F1: 0.4145
sub_12:Test (Best Model) - Loss: 1.2122 - Accuracy: 0.7246 - F1: 0.7376
sub_22:Test (Best Model) - Loss: 1.2810 - Accuracy: 0.4348 - F1: 0.3763
sub_16:Test (Best Model) - Loss: 1.1936 - Accuracy: 0.6324 - F1: 0.6257
sub_1:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.5507 - F1: 0.5730
sub_28:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3088 - F1: 0.2067
sub_15:Test (Best Model) - Loss: 1.2070 - Accuracy: 0.5735 - F1: 0.5932
sub_14:Test (Best Model) - Loss: 1.1731 - Accuracy: 0.5882 - F1: 0.5516
sub_29:Test (Best Model) - Loss: 1.1288 - Accuracy: 0.6765 - F1: 0.6933
sub_17:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3188 - F1: 0.3348
sub_19:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.6618 - F1: 0.6362
sub_8:Test (Best Model) - Loss: 1.2678 - Accuracy: 0.4853 - F1: 0.4792
sub_11:Test (Best Model) - Loss: 1.1839 - Accuracy: 0.6232 - F1: 0.6114
sub_20:Test (Best Model) - Loss: 1.2811 - Accuracy: 0.4638 - F1: 0.4683
sub_18:Test (Best Model) - Loss: 1.2391 - Accuracy: 0.5147 - F1: 0.4909
sub_2:Test (Best Model) - Loss: 1.2890 - Accuracy: 0.4412 - F1: 0.4336
sub_4:Test (Best Model) - Loss: 1.1984 - Accuracy: 0.6812 - F1: 0.6859
sub_27:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3188 - F1: 0.3348
sub_6:Test (Best Model) - Loss: 1.1632 - Accuracy: 0.5942 - F1: 0.5673
sub_13:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.4058 - F1: 0.3556
sub_21:Test (Best Model) - Loss: 1.2293 - Accuracy: 0.4706 - F1: 0.4394
sub_7:Test (Best Model) - Loss: 1.3328 - Accuracy: 0.4118 - F1: 0.4190
sub_23:Test (Best Model) - Loss: 1.3585 - Accuracy: 0.2794 - F1: 0.2032
sub_10:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.4706 - F1: 0.4253
sub_3:Test (Best Model) - Loss: 1.2344 - Accuracy: 0.6377 - F1: 0.6157
sub_12:Test (Best Model) - Loss: 1.2209 - Accuracy: 0.6377 - F1: 0.6252
sub_28:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.3088 - F1: 0.2022
sub_5:Test (Best Model) - Loss: 1.1173 - Accuracy: 0.6324 - F1: 0.6174
sub_24:Test (Best Model) - Loss: 1.2326 - Accuracy: 0.4853 - F1: 0.4635
sub_9:Test (Best Model) - Loss: 1.1009 - Accuracy: 0.5441 - F1: 0.5067
sub_22:Test (Best Model) - Loss: 1.2626 - Accuracy: 0.4265 - F1: 0.4073
sub_14:Test (Best Model) - Loss: 1.1994 - Accuracy: 0.6029 - F1: 0.5925
sub_25:Test (Best Model) - Loss: 1.2489 - Accuracy: 0.5000 - F1: 0.4678
sub_8:Test (Best Model) - Loss: 1.3030 - Accuracy: 0.5294 - F1: 0.4760
sub_26:Test (Best Model) - Loss: 1.1864 - Accuracy: 0.5588 - F1: 0.5248
sub_17:Test (Best Model) - Loss: 1.3011 - Accuracy: 0.3768 - F1: 0.3835
sub_20:Test (Best Model) - Loss: 1.2863 - Accuracy: 0.5362 - F1: 0.5329
sub_16:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.5000 - F1: 0.4917
sub_2:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.5652 - F1: 0.5535
sub_11:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.5797 - F1: 0.5338
sub_1:Test (Best Model) - Loss: 1.2656 - Accuracy: 0.5942 - F1: 0.5744
sub_29:Test (Best Model) - Loss: 1.1601 - Accuracy: 0.6029 - F1: 0.6357
sub_19:Test (Best Model) - Loss: 1.1806 - Accuracy: 0.5882 - F1: 0.5322
sub_15:Test (Best Model) - Loss: 1.2323 - Accuracy: 0.3971 - F1: 0.4147
sub_18:Test (Best Model) - Loss: 1.1991 - Accuracy: 0.5147 - F1: 0.4669
sub_6:Test (Best Model) - Loss: 1.2447 - Accuracy: 0.5362 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 1.2755 - Accuracy: 0.4853 - F1: 0.4234
sub_7:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.5735 - F1: 0.5575
sub_4:Test (Best Model) - Loss: 1.1983 - Accuracy: 0.5652 - F1: 0.5731
sub_27:Test (Best Model) - Loss: 1.3011 - Accuracy: 0.3768 - F1: 0.3835
sub_13:Test (Best Model) - Loss: 1.3368 - Accuracy: 0.4348 - F1: 0.3470
sub_9:Test (Best Model) - Loss: 1.1939 - Accuracy: 0.4853 - F1: 0.4470
sub_3:Test (Best Model) - Loss: 1.2342 - Accuracy: 0.5217 - F1: 0.5131
sub_21:Test (Best Model) - Loss: 1.1545 - Accuracy: 0.5588 - F1: 0.5598
sub_20:Test (Best Model) - Loss: 1.2953 - Accuracy: 0.5507 - F1: 0.5440
sub_28:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2794 - F1: 0.3059
sub_14:Test (Best Model) - Loss: 1.2125 - Accuracy: 0.5882 - F1: 0.6194
sub_24:Test (Best Model) - Loss: 1.2544 - Accuracy: 0.5147 - F1: 0.5197
sub_23:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2500 - F1: 0.1572
sub_11:Test (Best Model) - Loss: 1.2940 - Accuracy: 0.4493 - F1: 0.4452
sub_16:Test (Best Model) - Loss: 1.2767 - Accuracy: 0.5588 - F1: 0.5578
sub_8:Test (Best Model) - Loss: 1.2815 - Accuracy: 0.3529 - F1: 0.3596
sub_22:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.4706 - F1: 0.4471
sub_2:Test (Best Model) - Loss: 1.1862 - Accuracy: 0.6232 - F1: 0.6176
sub_29:Test (Best Model) - Loss: 1.2108 - Accuracy: 0.5735 - F1: 0.6006
sub_12:Test (Best Model) - Loss: 1.1686 - Accuracy: 0.6667 - F1: 0.6799
sub_10:Test (Best Model) - Loss: 1.2681 - Accuracy: 0.5362 - F1: 0.5064
sub_7:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.5294 - F1: 0.4976
sub_25:Test (Best Model) - Loss: 1.2035 - Accuracy: 0.5588 - F1: 0.5700
sub_5:Test (Best Model) - Loss: 1.1575 - Accuracy: 0.5882 - F1: 0.6025
sub_1:Test (Best Model) - Loss: 1.1533 - Accuracy: 0.6912 - F1: 0.6692
sub_26:Test (Best Model) - Loss: 1.2017 - Accuracy: 0.6324 - F1: 0.6098
sub_18:Test (Best Model) - Loss: 1.1848 - Accuracy: 0.6029 - F1: 0.5999
sub_15:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3382 - F1: 0.3009
sub_19:Test (Best Model) - Loss: 1.2335 - Accuracy: 0.5441 - F1: 0.4928
sub_24:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.4412 - F1: 0.4163
sub_4:Test (Best Model) - Loss: 1.1981 - Accuracy: 0.5362 - F1: 0.5347
sub_6:Test (Best Model) - Loss: 1.1927 - Accuracy: 0.5507 - F1: 0.5363
sub_17:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.4203 - F1: 0.4224
sub_20:Test (Best Model) - Loss: 1.2645 - Accuracy: 0.5217 - F1: 0.4933
sub_13:Test (Best Model) - Loss: 1.3079 - Accuracy: 0.3382 - F1: 0.3187
sub_22:Test (Best Model) - Loss: 1.2996 - Accuracy: 0.4559 - F1: 0.4044
sub_16:Test (Best Model) - Loss: 1.2711 - Accuracy: 0.5588 - F1: 0.5409
sub_23:Test (Best Model) - Loss: 1.2814 - Accuracy: 0.4638 - F1: 0.4174
sub_10:Test (Best Model) - Loss: 1.2563 - Accuracy: 0.6232 - F1: 0.5873
sub_28:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3088 - F1: 0.3163
sub_14:Test (Best Model) - Loss: 1.1682 - Accuracy: 0.5441 - F1: 0.5681
sub_3:Test (Best Model) - Loss: 1.2077 - Accuracy: 0.5652 - F1: 0.5687
sub_21:Test (Best Model) - Loss: 1.2490 - Accuracy: 0.5000 - F1: 0.4827
sub_5:Test (Best Model) - Loss: 1.2956 - Accuracy: 0.3971 - F1: 0.3013
sub_27:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.4203 - F1: 0.4224
sub_11:Test (Best Model) - Loss: 1.1778 - Accuracy: 0.6377 - F1: 0.6496
sub_12:Test (Best Model) - Loss: 1.2311 - Accuracy: 0.5441 - F1: 0.5285
sub_9:Test (Best Model) - Loss: 1.2451 - Accuracy: 0.3971 - F1: 0.3996
sub_8:Test (Best Model) - Loss: 1.2724 - Accuracy: 0.4706 - F1: 0.4432
sub_2:Test (Best Model) - Loss: 1.2371 - Accuracy: 0.5652 - F1: 0.5287
sub_1:Test (Best Model) - Loss: 1.1534 - Accuracy: 0.6618 - F1: 0.6524
sub_24:Test (Best Model) - Loss: 1.2425 - Accuracy: 0.5882 - F1: 0.5927
sub_7:Test (Best Model) - Loss: 1.1785 - Accuracy: 0.5735 - F1: 0.5887
sub_19:Test (Best Model) - Loss: 1.2460 - Accuracy: 0.5294 - F1: 0.4705
sub_4:Test (Best Model) - Loss: 1.2097 - Accuracy: 0.6377 - F1: 0.6117
sub_5:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.3676 - F1: 0.3086
sub_18:Test (Best Model) - Loss: 1.1320 - Accuracy: 0.6176 - F1: 0.5800
sub_6:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.5507 - F1: 0.5311
sub_13:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.3824 - F1: 0.3644
sub_15:Test (Best Model) - Loss: 1.3530 - Accuracy: 0.3529 - F1: 0.3186
sub_25:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.4118 - F1: 0.4209
sub_26:Test (Best Model) - Loss: 1.2008 - Accuracy: 0.4706 - F1: 0.4737
sub_14:Test (Best Model) - Loss: 1.2408 - Accuracy: 0.4559 - F1: 0.4251
sub_17:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.4706 - F1: 0.4783
sub_23:Test (Best Model) - Loss: 1.2492 - Accuracy: 0.4928 - F1: 0.4523
sub_28:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.3088 - F1: 0.2872
sub_22:Test (Best Model) - Loss: 1.2557 - Accuracy: 0.4706 - F1: 0.4378
sub_3:Test (Best Model) - Loss: 1.2130 - Accuracy: 0.5797 - F1: 0.5680
sub_20:Test (Best Model) - Loss: 1.2784 - Accuracy: 0.4928 - F1: 0.4804
sub_27:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.4706 - F1: 0.4783
sub_21:Test (Best Model) - Loss: 1.2303 - Accuracy: 0.5000 - F1: 0.4800
sub_12:Test (Best Model) - Loss: 1.2372 - Accuracy: 0.5000 - F1: 0.4888
sub_11:Test (Best Model) - Loss: 1.2743 - Accuracy: 0.5217 - F1: 0.4996
sub_29:Test (Best Model) - Loss: 1.1269 - Accuracy: 0.6812 - F1: 0.6833
sub_10:Test (Best Model) - Loss: 1.2435 - Accuracy: 0.5362 - F1: 0.4700
sub_16:Test (Best Model) - Loss: 1.2363 - Accuracy: 0.4853 - F1: 0.5062
sub_8:Test (Best Model) - Loss: 1.2942 - Accuracy: 0.3824 - F1: 0.3787
sub_7:Test (Best Model) - Loss: 1.2086 - Accuracy: 0.6176 - F1: 0.5859
sub_2:Test (Best Model) - Loss: 1.1795 - Accuracy: 0.6667 - F1: 0.6505
sub_26:Test (Best Model) - Loss: 1.2380 - Accuracy: 0.6324 - F1: 0.6517
sub_4:Test (Best Model) - Loss: 1.2277 - Accuracy: 0.6087 - F1: 0.6037
sub_24:Test (Best Model) - Loss: 1.1896 - Accuracy: 0.5735 - F1: 0.5710
sub_1:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.5882 - F1: 0.5441
sub_6:Test (Best Model) - Loss: 1.2462 - Accuracy: 0.5507 - F1: 0.5120
sub_9:Test (Best Model) - Loss: 1.2302 - Accuracy: 0.4265 - F1: 0.3995
sub_14:Test (Best Model) - Loss: 1.1631 - Accuracy: 0.5882 - F1: 0.5700
sub_22:Test (Best Model) - Loss: 1.3507 - Accuracy: 0.3676 - F1: 0.3325
sub_25:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.5294 - F1: 0.5376
sub_19:Test (Best Model) - Loss: 1.2407 - Accuracy: 0.5588 - F1: 0.5078
sub_18:Test (Best Model) - Loss: 1.2351 - Accuracy: 0.5735 - F1: 0.5295
sub_13:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.2941 - F1: 0.2652
sub_15:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.3824 - F1: 0.3276
sub_5:Test (Best Model) - Loss: 1.2521 - Accuracy: 0.4559 - F1: 0.3691
sub_28:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.1912 - F1: 0.1835
sub_10:Test (Best Model) - Loss: 1.2039 - Accuracy: 0.6087 - F1: 0.5853
sub_21:Test (Best Model) - Loss: 1.2824 - Accuracy: 0.5000 - F1: 0.4539
sub_29:Test (Best Model) - Loss: 1.1963 - Accuracy: 0.6087 - F1: 0.5764
sub_11:Test (Best Model) - Loss: 1.2117 - Accuracy: 0.5507 - F1: 0.5491
sub_17:Test (Best Model) - Loss: 1.2356 - Accuracy: 0.5735 - F1: 0.5752
sub_8:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.3824 - F1: 0.4027
sub_2:Test (Best Model) - Loss: 1.2958 - Accuracy: 0.4783 - F1: 0.4591
sub_7:Test (Best Model) - Loss: 1.2568 - Accuracy: 0.5588 - F1: 0.5656
sub_1:Test (Best Model) - Loss: 1.2038 - Accuracy: 0.6324 - F1: 0.5741
sub_27:Test (Best Model) - Loss: 1.2356 - Accuracy: 0.5735 - F1: 0.5752
sub_12:Test (Best Model) - Loss: 1.1966 - Accuracy: 0.6029 - F1: 0.5891
sub_23:Test (Best Model) - Loss: 1.2491 - Accuracy: 0.5072 - F1: 0.4790
sub_3:Test (Best Model) - Loss: 1.2206 - Accuracy: 0.4783 - F1: 0.4471
sub_26:Test (Best Model) - Loss: 1.1654 - Accuracy: 0.5441 - F1: 0.5459
sub_4:Test (Best Model) - Loss: 1.2704 - Accuracy: 0.5072 - F1: 0.5049
sub_16:Test (Best Model) - Loss: 1.2241 - Accuracy: 0.5735 - F1: 0.5397
sub_6:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.4638 - F1: 0.4691
sub_24:Test (Best Model) - Loss: 1.2495 - Accuracy: 0.5294 - F1: 0.5150
sub_9:Test (Best Model) - Loss: 1.2393 - Accuracy: 0.5147 - F1: 0.4924
sub_13:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.2941 - F1: 0.2651
sub_14:Test (Best Model) - Loss: 1.2288 - Accuracy: 0.5147 - F1: 0.5400
sub_10:Test (Best Model) - Loss: 1.2174 - Accuracy: 0.5942 - F1: 0.5729
sub_8:Test (Best Model) - Loss: 1.3428 - Accuracy: 0.4412 - F1: 0.4147
sub_15:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.3382 - F1: 0.2610
sub_5:Test (Best Model) - Loss: 1.2161 - Accuracy: 0.5147 - F1: 0.4426
sub_19:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.5441 - F1: 0.4891
sub_21:Test (Best Model) - Loss: 1.2465 - Accuracy: 0.5000 - F1: 0.4842
sub_25:Test (Best Model) - Loss: 1.2215 - Accuracy: 0.5441 - F1: 0.5691
sub_26:Test (Best Model) - Loss: 1.2535 - Accuracy: 0.4118 - F1: 0.4051
sub_28:Test (Best Model) - Loss: 1.4984 - Accuracy: 0.1324 - F1: 0.1152
sub_29:Test (Best Model) - Loss: 1.1849 - Accuracy: 0.6522 - F1: 0.6476
sub_12:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.5294 - F1: 0.4972
sub_16:Test (Best Model) - Loss: 1.2154 - Accuracy: 0.5735 - F1: 0.5625
sub_17:Test (Best Model) - Loss: 1.2796 - Accuracy: 0.5735 - F1: 0.5795
sub_1:Test (Best Model) - Loss: 1.1870 - Accuracy: 0.6471 - F1: 0.6138
sub_23:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.4638 - F1: 0.4252
sub_27:Test (Best Model) - Loss: 1.2796 - Accuracy: 0.5735 - F1: 0.5795
sub_13:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.3088 - F1: 0.2736
sub_9:Test (Best Model) - Loss: 1.2465 - Accuracy: 0.5000 - F1: 0.4782
sub_11:Test (Best Model) - Loss: 1.1758 - Accuracy: 0.6232 - F1: 0.6349
sub_3:Test (Best Model) - Loss: 1.1897 - Accuracy: 0.5362 - F1: 0.5208
sub_24:Test (Best Model) - Loss: 1.1305 - Accuracy: 0.6176 - F1: 0.6224
sub_25:Test (Best Model) - Loss: 1.3121 - Accuracy: 0.5000 - F1: 0.5265
sub_5:Test (Best Model) - Loss: 1.2380 - Accuracy: 0.5441 - F1: 0.4851
sub_12:Test (Best Model) - Loss: 1.2619 - Accuracy: 0.5441 - F1: 0.5507
sub_16:Test (Best Model) - Loss: 1.2934 - Accuracy: 0.4559 - F1: 0.4518
sub_21:Test (Best Model) - Loss: 1.2353 - Accuracy: 0.5441 - F1: 0.5277
sub_23:Test (Best Model) - Loss: 1.2774 - Accuracy: 0.5072 - F1: 0.4622
sub_15:Test (Best Model) - Loss: 1.4087 - Accuracy: 0.3676 - F1: 0.3065
sub_29:Test (Best Model) - Loss: 1.1592 - Accuracy: 0.6087 - F1: 0.6141
sub_24:Test (Best Model) - Loss: 1.2506 - Accuracy: 0.5735 - F1: 0.5833
sub_27:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.5441 - F1: 0.5526
sub_17:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.5441 - F1: 0.5526
sub_3:Test (Best Model) - Loss: 1.2716 - Accuracy: 0.4638 - F1: 0.4543
sub_9:Test (Best Model) - Loss: 1.2408 - Accuracy: 0.4853 - F1: 0.4728
sub_27:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.3676 - F1: 0.3937
sub_17:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.3676 - F1: 0.3937
sub_29:Test (Best Model) - Loss: 1.2359 - Accuracy: 0.5797 - F1: 0.5855

=== Summary Results ===

acc: 51.63 ± 6.28
F1: 49.84 ± 7.01
acc-in: 72.77 ± 6.73
F1-in: 71.89 ± 7.04
