lr: 0.0001
sub_10:Test (Best Model) - Loss: 1.2478 - Accuracy: 0.4559 - F1: 0.4954
sub_11:Test (Best Model) - Loss: 1.1904 - Accuracy: 0.5797 - F1: 0.5574
sub_22:Test (Best Model) - Loss: 1.2639 - Accuracy: 0.4559 - F1: 0.4145
sub_28:Test (Best Model) - Loss: 1.2076 - Accuracy: 0.6765 - F1: 0.6142
sub_3:Test (Best Model) - Loss: 1.1181 - Accuracy: 0.6912 - F1: 0.6472
sub_24:Test (Best Model) - Loss: 1.1469 - Accuracy: 0.6765 - F1: 0.6530
sub_8:Test (Best Model) - Loss: 1.2464 - Accuracy: 0.5588 - F1: 0.5352
sub_19:Test (Best Model) - Loss: 1.2499 - Accuracy: 0.4265 - F1: 0.3628
sub_6:Test (Best Model) - Loss: 1.2516 - Accuracy: 0.4853 - F1: 0.4365
sub_7:Test (Best Model) - Loss: 1.0239 - Accuracy: 0.9265 - F1: 0.9229
sub_1:Test (Best Model) - Loss: 1.1454 - Accuracy: 0.6765 - F1: 0.6886
sub_25:Test (Best Model) - Loss: 1.0072 - Accuracy: 0.9420 - F1: 0.9384
sub_20:Test (Best Model) - Loss: 1.1415 - Accuracy: 0.6765 - F1: 0.6269
sub_14:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.4706 - F1: 0.3921
sub_12:Test (Best Model) - Loss: 1.1638 - Accuracy: 0.7059 - F1: 0.6985
sub_4:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.6232 - F1: 0.5929
sub_16:Test (Best Model) - Loss: 1.0789 - Accuracy: 0.7353 - F1: 0.7347
sub_10:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.4412 - F1: 0.4579
sub_17:Test (Best Model) - Loss: 1.0909 - Accuracy: 0.7971 - F1: 0.7976
sub_9:Test (Best Model) - Loss: 1.1123 - Accuracy: 0.6618 - F1: 0.6821
sub_26:Test (Best Model) - Loss: 1.1254 - Accuracy: 0.6232 - F1: 0.6449
sub_18:Test (Best Model) - Loss: 1.1213 - Accuracy: 0.7246 - F1: 0.7094
sub_13:Test (Best Model) - Loss: 1.2193 - Accuracy: 0.5441 - F1: 0.4976
sub_29:Test (Best Model) - Loss: 1.1437 - Accuracy: 0.5588 - F1: 0.5947
sub_5:Test (Best Model) - Loss: 1.1988 - Accuracy: 0.6912 - F1: 0.6352
sub_27:Test (Best Model) - Loss: 1.0909 - Accuracy: 0.7971 - F1: 0.7976
sub_21:Test (Best Model) - Loss: 1.1579 - Accuracy: 0.7059 - F1: 0.7168
sub_2:Test (Best Model) - Loss: 1.0776 - Accuracy: 0.6957 - F1: 0.6848
sub_23:Test (Best Model) - Loss: 1.0876 - Accuracy: 0.7101 - F1: 0.6643
sub_22:Test (Best Model) - Loss: 1.3174 - Accuracy: 0.4706 - F1: 0.4133
sub_8:Test (Best Model) - Loss: 1.3060 - Accuracy: 0.4559 - F1: 0.4068
sub_28:Test (Best Model) - Loss: 1.2524 - Accuracy: 0.6176 - F1: 0.5376
sub_19:Test (Best Model) - Loss: 1.3236 - Accuracy: 0.3235 - F1: 0.2468
sub_11:Test (Best Model) - Loss: 1.0707 - Accuracy: 0.7681 - F1: 0.7679
sub_25:Test (Best Model) - Loss: 1.0360 - Accuracy: 0.8841 - F1: 0.8842
sub_4:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.6667 - F1: 0.6304
sub_10:Test (Best Model) - Loss: 1.2510 - Accuracy: 0.4706 - F1: 0.4921
sub_6:Test (Best Model) - Loss: 1.1995 - Accuracy: 0.5294 - F1: 0.5052
sub_24:Test (Best Model) - Loss: 1.1987 - Accuracy: 0.6324 - F1: 0.6089
sub_12:Test (Best Model) - Loss: 1.1193 - Accuracy: 0.6029 - F1: 0.5810
sub_14:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.4265 - F1: 0.3416
sub_1:Test (Best Model) - Loss: 1.1046 - Accuracy: 0.5882 - F1: 0.5667
sub_16:Test (Best Model) - Loss: 1.1323 - Accuracy: 0.6912 - F1: 0.6922
sub_13:Test (Best Model) - Loss: 1.2167 - Accuracy: 0.5147 - F1: 0.4750
sub_7:Test (Best Model) - Loss: 1.0038 - Accuracy: 0.9559 - F1: 0.9508
sub_15:Test (Best Model) - Loss: 1.0734 - Accuracy: 0.7059 - F1: 0.7137
sub_17:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.7101 - F1: 0.6767
sub_20:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.5882 - F1: 0.5508
sub_9:Test (Best Model) - Loss: 1.1910 - Accuracy: 0.5588 - F1: 0.5595
sub_29:Test (Best Model) - Loss: 1.1744 - Accuracy: 0.5441 - F1: 0.5129
sub_5:Test (Best Model) - Loss: 1.1930 - Accuracy: 0.7206 - F1: 0.6503
sub_23:Test (Best Model) - Loss: 1.0886 - Accuracy: 0.7971 - F1: 0.8054
sub_22:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.4265 - F1: 0.3725
sub_26:Test (Best Model) - Loss: 1.1184 - Accuracy: 0.6087 - F1: 0.6320
sub_8:Test (Best Model) - Loss: 1.2810 - Accuracy: 0.4706 - F1: 0.4407
sub_27:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.7101 - F1: 0.6767
sub_3:Test (Best Model) - Loss: 1.1293 - Accuracy: 0.6912 - F1: 0.6374
sub_18:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.7536 - F1: 0.7649
sub_2:Test (Best Model) - Loss: 1.1655 - Accuracy: 0.5652 - F1: 0.5261
sub_10:Test (Best Model) - Loss: 1.3023 - Accuracy: 0.4559 - F1: 0.4887
sub_11:Test (Best Model) - Loss: 1.1539 - Accuracy: 0.6232 - F1: 0.6297
sub_21:Test (Best Model) - Loss: 1.0691 - Accuracy: 0.8235 - F1: 0.8104
sub_25:Test (Best Model) - Loss: 1.0404 - Accuracy: 0.8696 - F1: 0.8621
sub_19:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.3088 - F1: 0.2415
sub_28:Test (Best Model) - Loss: 1.2107 - Accuracy: 0.6912 - F1: 0.6040
sub_16:Test (Best Model) - Loss: 1.1648 - Accuracy: 0.6324 - F1: 0.6417
sub_4:Test (Best Model) - Loss: 1.1492 - Accuracy: 0.6377 - F1: 0.5819
sub_24:Test (Best Model) - Loss: 1.1636 - Accuracy: 0.6029 - F1: 0.5789
sub_12:Test (Best Model) - Loss: 1.1435 - Accuracy: 0.6471 - F1: 0.6539
sub_6:Test (Best Model) - Loss: 1.2446 - Accuracy: 0.4118 - F1: 0.3553
sub_8:Test (Best Model) - Loss: 1.2602 - Accuracy: 0.5588 - F1: 0.5268
sub_5:Test (Best Model) - Loss: 1.2132 - Accuracy: 0.7353 - F1: 0.6631
sub_1:Test (Best Model) - Loss: 1.1522 - Accuracy: 0.6176 - F1: 0.6052
sub_15:Test (Best Model) - Loss: 1.1220 - Accuracy: 0.7647 - F1: 0.7707
sub_9:Test (Best Model) - Loss: 1.2093 - Accuracy: 0.5441 - F1: 0.5558
sub_14:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4265 - F1: 0.3504
sub_17:Test (Best Model) - Loss: 1.0934 - Accuracy: 0.7826 - F1: 0.7784
sub_26:Test (Best Model) - Loss: 1.1608 - Accuracy: 0.6667 - F1: 0.6899
sub_7:Test (Best Model) - Loss: 1.0220 - Accuracy: 0.9706 - F1: 0.9676
sub_20:Test (Best Model) - Loss: 1.1260 - Accuracy: 0.6618 - F1: 0.6168
sub_27:Test (Best Model) - Loss: 1.0934 - Accuracy: 0.7826 - F1: 0.7784
sub_29:Test (Best Model) - Loss: 1.1402 - Accuracy: 0.5147 - F1: 0.5427
sub_3:Test (Best Model) - Loss: 1.1021 - Accuracy: 0.7794 - F1: 0.7776
sub_13:Test (Best Model) - Loss: 1.2033 - Accuracy: 0.6176 - F1: 0.5623
sub_2:Test (Best Model) - Loss: 1.2033 - Accuracy: 0.4493 - F1: 0.3841
sub_10:Test (Best Model) - Loss: 1.2273 - Accuracy: 0.4706 - F1: 0.5111
sub_22:Test (Best Model) - Loss: 1.2562 - Accuracy: 0.4412 - F1: 0.4352
sub_18:Test (Best Model) - Loss: 1.0708 - Accuracy: 0.7971 - F1: 0.7977
sub_23:Test (Best Model) - Loss: 0.9841 - Accuracy: 0.7391 - F1: 0.6964
sub_21:Test (Best Model) - Loss: 1.1281 - Accuracy: 0.7500 - F1: 0.7642
sub_6:Test (Best Model) - Loss: 1.1660 - Accuracy: 0.5882 - F1: 0.5372
sub_25:Test (Best Model) - Loss: 1.0124 - Accuracy: 0.9130 - F1: 0.9119
sub_28:Test (Best Model) - Loss: 1.2761 - Accuracy: 0.5588 - F1: 0.5004
sub_16:Test (Best Model) - Loss: 1.1452 - Accuracy: 0.6618 - F1: 0.6654
sub_19:Test (Best Model) - Loss: 1.2770 - Accuracy: 0.4118 - F1: 0.3818
sub_5:Test (Best Model) - Loss: 1.2211 - Accuracy: 0.6471 - F1: 0.6030
sub_9:Test (Best Model) - Loss: 1.2001 - Accuracy: 0.6176 - F1: 0.6450
sub_20:Test (Best Model) - Loss: 1.1096 - Accuracy: 0.6176 - F1: 0.5625
sub_12:Test (Best Model) - Loss: 1.1128 - Accuracy: 0.6029 - F1: 0.5950
sub_4:Test (Best Model) - Loss: 1.0490 - Accuracy: 0.6667 - F1: 0.6222
sub_11:Test (Best Model) - Loss: 1.1001 - Accuracy: 0.7826 - F1: 0.7856
sub_29:Test (Best Model) - Loss: 1.1648 - Accuracy: 0.6029 - F1: 0.6162
sub_8:Test (Best Model) - Loss: 1.2266 - Accuracy: 0.5147 - F1: 0.4925
sub_1:Test (Best Model) - Loss: 1.1544 - Accuracy: 0.5588 - F1: 0.5506
sub_2:Test (Best Model) - Loss: 1.1299 - Accuracy: 0.6667 - F1: 0.6377
sub_26:Test (Best Model) - Loss: 1.1067 - Accuracy: 0.6812 - F1: 0.6998
sub_7:Test (Best Model) - Loss: 1.0117 - Accuracy: 0.9118 - F1: 0.9013
sub_14:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.4706 - F1: 0.3843
sub_15:Test (Best Model) - Loss: 1.1362 - Accuracy: 0.7206 - F1: 0.7175
sub_24:Test (Best Model) - Loss: 1.1878 - Accuracy: 0.5588 - F1: 0.5164
sub_3:Test (Best Model) - Loss: 1.1222 - Accuracy: 0.7059 - F1: 0.6723
sub_10:Test (Best Model) - Loss: 1.1013 - Accuracy: 0.7794 - F1: 0.7903
sub_17:Test (Best Model) - Loss: 0.9748 - Accuracy: 0.7826 - F1: 0.7868
sub_6:Test (Best Model) - Loss: 1.1929 - Accuracy: 0.6618 - F1: 0.5945
sub_5:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.6618 - F1: 0.6159
sub_19:Test (Best Model) - Loss: 1.2946 - Accuracy: 0.2941 - F1: 0.2362
sub_27:Test (Best Model) - Loss: 0.9748 - Accuracy: 0.7826 - F1: 0.7868
sub_25:Test (Best Model) - Loss: 1.0303 - Accuracy: 0.8696 - F1: 0.8633
sub_18:Test (Best Model) - Loss: 1.1279 - Accuracy: 0.6667 - F1: 0.6908
sub_13:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.5735 - F1: 0.5203
sub_16:Test (Best Model) - Loss: 1.1330 - Accuracy: 0.6765 - F1: 0.6353
sub_23:Test (Best Model) - Loss: 1.1514 - Accuracy: 0.6667 - F1: 0.6706
sub_28:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.5000 - F1: 0.4352
sub_22:Test (Best Model) - Loss: 1.2725 - Accuracy: 0.4706 - F1: 0.4273
sub_12:Test (Best Model) - Loss: 1.1051 - Accuracy: 0.7059 - F1: 0.6432
sub_20:Test (Best Model) - Loss: 1.1588 - Accuracy: 0.6029 - F1: 0.5495
sub_8:Test (Best Model) - Loss: 1.0876 - Accuracy: 0.6471 - F1: 0.6334
sub_26:Test (Best Model) - Loss: 1.1326 - Accuracy: 0.6667 - F1: 0.6759
sub_11:Test (Best Model) - Loss: 1.0609 - Accuracy: 0.8696 - F1: 0.8733
sub_9:Test (Best Model) - Loss: 1.1018 - Accuracy: 0.6029 - F1: 0.6054
sub_21:Test (Best Model) - Loss: 1.0276 - Accuracy: 0.7794 - F1: 0.7788
sub_14:Test (Best Model) - Loss: 1.2569 - Accuracy: 0.4412 - F1: 0.3749
sub_2:Test (Best Model) - Loss: 1.1293 - Accuracy: 0.5942 - F1: 0.5074
sub_29:Test (Best Model) - Loss: 1.1469 - Accuracy: 0.5000 - F1: 0.5344
sub_3:Test (Best Model) - Loss: 1.1366 - Accuracy: 0.7206 - F1: 0.7143
sub_6:Test (Best Model) - Loss: 1.1625 - Accuracy: 0.6667 - F1: 0.6569
sub_16:Test (Best Model) - Loss: 1.1240 - Accuracy: 0.7353 - F1: 0.7295
sub_1:Test (Best Model) - Loss: 1.0704 - Accuracy: 0.6176 - F1: 0.6089
sub_24:Test (Best Model) - Loss: 1.1144 - Accuracy: 0.6471 - F1: 0.6468
sub_4:Test (Best Model) - Loss: 1.0354 - Accuracy: 0.6377 - F1: 0.5788
sub_5:Test (Best Model) - Loss: 1.0905 - Accuracy: 0.7206 - F1: 0.6449
sub_10:Test (Best Model) - Loss: 1.1370 - Accuracy: 0.6176 - F1: 0.5544
sub_20:Test (Best Model) - Loss: 1.0460 - Accuracy: 0.7206 - F1: 0.6849
sub_12:Test (Best Model) - Loss: 1.0979 - Accuracy: 0.7681 - F1: 0.7590
sub_7:Test (Best Model) - Loss: 0.9625 - Accuracy: 0.9412 - F1: 0.9333
sub_28:Test (Best Model) - Loss: 1.3377 - Accuracy: 0.3971 - F1: 0.3286
sub_22:Test (Best Model) - Loss: 1.1986 - Accuracy: 0.4928 - F1: 0.4473
sub_8:Test (Best Model) - Loss: 1.1318 - Accuracy: 0.6765 - F1: 0.6220
sub_25:Test (Best Model) - Loss: 1.0201 - Accuracy: 0.7794 - F1: 0.7678
sub_18:Test (Best Model) - Loss: 1.1199 - Accuracy: 0.7391 - F1: 0.7431
sub_17:Test (Best Model) - Loss: 1.0519 - Accuracy: 0.7246 - F1: 0.7053
sub_23:Test (Best Model) - Loss: 1.1086 - Accuracy: 0.4928 - F1: 0.4327
sub_27:Test (Best Model) - Loss: 1.0519 - Accuracy: 0.7246 - F1: 0.7053
sub_15:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.6765 - F1: 0.6882
sub_26:Test (Best Model) - Loss: 1.0931 - Accuracy: 0.6324 - F1: 0.6234
sub_19:Test (Best Model) - Loss: 1.1332 - Accuracy: 0.5735 - F1: 0.5407
sub_9:Test (Best Model) - Loss: 1.1093 - Accuracy: 0.6176 - F1: 0.5960
sub_2:Test (Best Model) - Loss: 1.0773 - Accuracy: 0.7794 - F1: 0.7722
sub_29:Test (Best Model) - Loss: 1.0488 - Accuracy: 0.7647 - F1: 0.7719
sub_11:Test (Best Model) - Loss: 1.0755 - Accuracy: 0.6812 - F1: 0.6502
sub_12:Test (Best Model) - Loss: 1.1805 - Accuracy: 0.6957 - F1: 0.7062
sub_16:Test (Best Model) - Loss: 1.1390 - Accuracy: 0.6618 - F1: 0.6588
sub_3:Test (Best Model) - Loss: 1.1643 - Accuracy: 0.6087 - F1: 0.5735
sub_14:Test (Best Model) - Loss: 1.1125 - Accuracy: 0.5735 - F1: 0.6054
sub_21:Test (Best Model) - Loss: 1.0970 - Accuracy: 0.7206 - F1: 0.7184
sub_13:Test (Best Model) - Loss: 1.1904 - Accuracy: 0.5735 - F1: 0.5158
sub_20:Test (Best Model) - Loss: 1.0927 - Accuracy: 0.6618 - F1: 0.6288
sub_6:Test (Best Model) - Loss: 1.1107 - Accuracy: 0.6957 - F1: 0.6752
sub_4:Test (Best Model) - Loss: 1.0547 - Accuracy: 0.7971 - F1: 0.8017
sub_10:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.4853 - F1: 0.5008
sub_23:Test (Best Model) - Loss: 1.2155 - Accuracy: 0.5588 - F1: 0.5201
sub_5:Test (Best Model) - Loss: 1.1058 - Accuracy: 0.7059 - F1: 0.6460
sub_1:Test (Best Model) - Loss: 1.0847 - Accuracy: 0.5797 - F1: 0.5716
sub_24:Test (Best Model) - Loss: 1.1037 - Accuracy: 0.7059 - F1: 0.6173
sub_7:Test (Best Model) - Loss: 1.1288 - Accuracy: 0.7206 - F1: 0.6375
sub_25:Test (Best Model) - Loss: 1.0845 - Accuracy: 0.7941 - F1: 0.7709
sub_8:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.6765 - F1: 0.6137
sub_28:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.3971 - F1: 0.3207
sub_22:Test (Best Model) - Loss: 1.2117 - Accuracy: 0.4783 - F1: 0.4240
sub_12:Test (Best Model) - Loss: 1.1845 - Accuracy: 0.5507 - F1: 0.5420
sub_27:Test (Best Model) - Loss: 1.1515 - Accuracy: 0.5652 - F1: 0.4951
sub_17:Test (Best Model) - Loss: 1.1515 - Accuracy: 0.5652 - F1: 0.4951
sub_18:Test (Best Model) - Loss: 1.1524 - Accuracy: 0.5588 - F1: 0.5740
sub_19:Test (Best Model) - Loss: 1.1430 - Accuracy: 0.6324 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 1.1972 - Accuracy: 0.6765 - F1: 0.6427
sub_15:Test (Best Model) - Loss: 1.0552 - Accuracy: 0.6471 - F1: 0.6135
sub_9:Test (Best Model) - Loss: 1.0775 - Accuracy: 0.6324 - F1: 0.5701
sub_26:Test (Best Model) - Loss: 1.1323 - Accuracy: 0.6765 - F1: 0.6538
sub_21:Test (Best Model) - Loss: 1.0371 - Accuracy: 0.8088 - F1: 0.8088
sub_20:Test (Best Model) - Loss: 1.1126 - Accuracy: 0.6324 - F1: 0.6036
sub_3:Test (Best Model) - Loss: 1.1845 - Accuracy: 0.6377 - F1: 0.6126
sub_2:Test (Best Model) - Loss: 1.0450 - Accuracy: 0.6912 - F1: 0.6397
sub_1:Test (Best Model) - Loss: 1.1853 - Accuracy: 0.5507 - F1: 0.5380
sub_11:Test (Best Model) - Loss: 1.0685 - Accuracy: 0.7246 - F1: 0.6845
sub_13:Test (Best Model) - Loss: 1.1671 - Accuracy: 0.5362 - F1: 0.5538
sub_4:Test (Best Model) - Loss: 1.0376 - Accuracy: 0.8116 - F1: 0.8014
sub_29:Test (Best Model) - Loss: 0.9534 - Accuracy: 0.8824 - F1: 0.8857
sub_14:Test (Best Model) - Loss: 1.1585 - Accuracy: 0.4853 - F1: 0.4870
sub_10:Test (Best Model) - Loss: 1.1591 - Accuracy: 0.6176 - F1: 0.6217
sub_24:Test (Best Model) - Loss: 1.1514 - Accuracy: 0.7059 - F1: 0.7103
sub_25:Test (Best Model) - Loss: 1.0740 - Accuracy: 0.7941 - F1: 0.7834
sub_5:Test (Best Model) - Loss: 1.1461 - Accuracy: 0.6765 - F1: 0.6385
sub_8:Test (Best Model) - Loss: 1.1125 - Accuracy: 0.6765 - F1: 0.6520
sub_23:Test (Best Model) - Loss: 1.2510 - Accuracy: 0.5147 - F1: 0.4519
sub_16:Test (Best Model) - Loss: 1.2053 - Accuracy: 0.6618 - F1: 0.6142
sub_27:Test (Best Model) - Loss: 1.2447 - Accuracy: 0.4928 - F1: 0.4174
sub_7:Test (Best Model) - Loss: 1.1730 - Accuracy: 0.6765 - F1: 0.5920
sub_19:Test (Best Model) - Loss: 1.1842 - Accuracy: 0.7059 - F1: 0.7122
sub_18:Test (Best Model) - Loss: 1.1588 - Accuracy: 0.5735 - F1: 0.5868
sub_17:Test (Best Model) - Loss: 1.2447 - Accuracy: 0.4928 - F1: 0.4174
sub_9:Test (Best Model) - Loss: 1.1151 - Accuracy: 0.7353 - F1: 0.7090
sub_28:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.2794 - F1: 0.1406
sub_22:Test (Best Model) - Loss: 1.2331 - Accuracy: 0.5507 - F1: 0.5028
sub_6:Test (Best Model) - Loss: 1.1283 - Accuracy: 0.5797 - F1: 0.5236
sub_3:Test (Best Model) - Loss: 1.2414 - Accuracy: 0.5507 - F1: 0.5150
sub_1:Test (Best Model) - Loss: 1.2008 - Accuracy: 0.5507 - F1: 0.5281
sub_21:Test (Best Model) - Loss: 1.0354 - Accuracy: 0.7941 - F1: 0.7853
sub_13:Test (Best Model) - Loss: 1.2133 - Accuracy: 0.5217 - F1: 0.4213
sub_10:Test (Best Model) - Loss: 1.2245 - Accuracy: 0.5294 - F1: 0.5185
sub_5:Test (Best Model) - Loss: 1.1121 - Accuracy: 0.7206 - F1: 0.6565
sub_2:Test (Best Model) - Loss: 1.0741 - Accuracy: 0.6618 - F1: 0.5929
sub_23:Test (Best Model) - Loss: 1.2840 - Accuracy: 0.3971 - F1: 0.3189
sub_15:Test (Best Model) - Loss: 1.0901 - Accuracy: 0.7353 - F1: 0.7102
sub_26:Test (Best Model) - Loss: 1.1746 - Accuracy: 0.5882 - F1: 0.5160
sub_12:Test (Best Model) - Loss: 1.0658 - Accuracy: 0.7391 - F1: 0.7456
sub_20:Test (Best Model) - Loss: 1.1328 - Accuracy: 0.5588 - F1: 0.5047
sub_4:Test (Best Model) - Loss: 1.1235 - Accuracy: 0.8261 - F1: 0.8093
sub_24:Test (Best Model) - Loss: 1.1473 - Accuracy: 0.6765 - F1: 0.6181
sub_11:Test (Best Model) - Loss: 1.0672 - Accuracy: 0.7391 - F1: 0.7160
sub_28:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.3235 - F1: 0.2327
sub_14:Test (Best Model) - Loss: 1.1206 - Accuracy: 0.6176 - F1: 0.6414
sub_16:Test (Best Model) - Loss: 1.2132 - Accuracy: 0.6029 - F1: 0.5801
sub_27:Test (Best Model) - Loss: 1.2176 - Accuracy: 0.5217 - F1: 0.5018
sub_25:Test (Best Model) - Loss: 1.0376 - Accuracy: 0.8088 - F1: 0.7924
sub_7:Test (Best Model) - Loss: 1.1643 - Accuracy: 0.6765 - F1: 0.6280
sub_18:Test (Best Model) - Loss: 1.2969 - Accuracy: 0.4706 - F1: 0.4181
sub_17:Test (Best Model) - Loss: 1.2176 - Accuracy: 0.5217 - F1: 0.5018
sub_9:Test (Best Model) - Loss: 1.1257 - Accuracy: 0.7941 - F1: 0.7969
sub_19:Test (Best Model) - Loss: 1.1660 - Accuracy: 0.6765 - F1: 0.6766
sub_29:Test (Best Model) - Loss: 0.9895 - Accuracy: 0.8824 - F1: 0.8861
sub_8:Test (Best Model) - Loss: 1.0635 - Accuracy: 0.7206 - F1: 0.7052
sub_26:Test (Best Model) - Loss: 1.1605 - Accuracy: 0.6618 - F1: 0.6608
sub_20:Test (Best Model) - Loss: 1.1175 - Accuracy: 0.7206 - F1: 0.7141
sub_3:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.6087 - F1: 0.5799
sub_12:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.7826 - F1: 0.7849
sub_1:Test (Best Model) - Loss: 1.1612 - Accuracy: 0.5942 - F1: 0.5569
sub_22:Test (Best Model) - Loss: 1.2020 - Accuracy: 0.5217 - F1: 0.4774
sub_6:Test (Best Model) - Loss: 1.1177 - Accuracy: 0.7681 - F1: 0.7623
sub_10:Test (Best Model) - Loss: 1.1359 - Accuracy: 0.6667 - F1: 0.6042
sub_28:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3235 - F1: 0.2322
sub_2:Test (Best Model) - Loss: 1.1038 - Accuracy: 0.6618 - F1: 0.5860
sub_24:Test (Best Model) - Loss: 1.1593 - Accuracy: 0.7059 - F1: 0.6624
sub_14:Test (Best Model) - Loss: 1.1797 - Accuracy: 0.6029 - F1: 0.6267
sub_18:Test (Best Model) - Loss: 1.2419 - Accuracy: 0.5441 - F1: 0.5855
sub_13:Test (Best Model) - Loss: 1.2072 - Accuracy: 0.6087 - F1: 0.5878
sub_23:Test (Best Model) - Loss: 1.2689 - Accuracy: 0.5294 - F1: 0.4786
sub_21:Test (Best Model) - Loss: 0.9833 - Accuracy: 0.8382 - F1: 0.8323
sub_4:Test (Best Model) - Loss: 1.0333 - Accuracy: 0.8261 - F1: 0.8194
sub_11:Test (Best Model) - Loss: 1.1157 - Accuracy: 0.7246 - F1: 0.6608
sub_5:Test (Best Model) - Loss: 1.0350 - Accuracy: 0.8088 - F1: 0.8031
sub_16:Test (Best Model) - Loss: 1.1669 - Accuracy: 0.5735 - F1: 0.5640
sub_27:Test (Best Model) - Loss: 1.2156 - Accuracy: 0.4928 - F1: 0.4385
sub_15:Test (Best Model) - Loss: 1.0575 - Accuracy: 0.7353 - F1: 0.7173
sub_7:Test (Best Model) - Loss: 1.1794 - Accuracy: 0.6324 - F1: 0.5803
sub_25:Test (Best Model) - Loss: 1.1122 - Accuracy: 0.7500 - F1: 0.7165
sub_17:Test (Best Model) - Loss: 1.2156 - Accuracy: 0.4928 - F1: 0.4385
sub_6:Test (Best Model) - Loss: 1.1357 - Accuracy: 0.6377 - F1: 0.6255
sub_8:Test (Best Model) - Loss: 1.1313 - Accuracy: 0.5294 - F1: 0.5547
sub_20:Test (Best Model) - Loss: 1.1367 - Accuracy: 0.6522 - F1: 0.6200
sub_22:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.4493 - F1: 0.4130
sub_26:Test (Best Model) - Loss: 1.1688 - Accuracy: 0.5294 - F1: 0.5125
sub_3:Test (Best Model) - Loss: 1.1884 - Accuracy: 0.6087 - F1: 0.5667
sub_28:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.4118 - F1: 0.2757
sub_29:Test (Best Model) - Loss: 1.0000 - Accuracy: 0.8824 - F1: 0.8857
sub_9:Test (Best Model) - Loss: 1.0518 - Accuracy: 0.5735 - F1: 0.5483
sub_12:Test (Best Model) - Loss: 1.0917 - Accuracy: 0.7500 - F1: 0.7693
sub_10:Test (Best Model) - Loss: 1.0945 - Accuracy: 0.7391 - F1: 0.6929
sub_19:Test (Best Model) - Loss: 1.1135 - Accuracy: 0.6029 - F1: 0.5883
sub_11:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.7246 - F1: 0.7013
sub_18:Test (Best Model) - Loss: 1.2072 - Accuracy: 0.6029 - F1: 0.6152
sub_1:Test (Best Model) - Loss: 1.1286 - Accuracy: 0.6377 - F1: 0.6039
sub_24:Test (Best Model) - Loss: 1.1618 - Accuracy: 0.6912 - F1: 0.6657
sub_21:Test (Best Model) - Loss: 1.0516 - Accuracy: 0.7941 - F1: 0.7811
sub_14:Test (Best Model) - Loss: 1.2162 - Accuracy: 0.5147 - F1: 0.5093
sub_13:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.5652 - F1: 0.5479
sub_2:Test (Best Model) - Loss: 1.0372 - Accuracy: 0.7941 - F1: 0.7913
sub_23:Test (Best Model) - Loss: 1.2135 - Accuracy: 0.6324 - F1: 0.5713
sub_25:Test (Best Model) - Loss: 1.0817 - Accuracy: 0.7500 - F1: 0.7554
sub_6:Test (Best Model) - Loss: 1.0769 - Accuracy: 0.7101 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.7500 - F1: 0.7705
sub_16:Test (Best Model) - Loss: 1.1583 - Accuracy: 0.6618 - F1: 0.6661
sub_5:Test (Best Model) - Loss: 1.1162 - Accuracy: 0.7059 - F1: 0.6233
sub_22:Test (Best Model) - Loss: 1.2006 - Accuracy: 0.6471 - F1: 0.6545
sub_4:Test (Best Model) - Loss: 0.9598 - Accuracy: 0.8696 - F1: 0.8741
sub_7:Test (Best Model) - Loss: 1.1163 - Accuracy: 0.7794 - F1: 0.7481
sub_20:Test (Best Model) - Loss: 1.0362 - Accuracy: 0.7536 - F1: 0.7563
sub_27:Test (Best Model) - Loss: 1.1841 - Accuracy: 0.5507 - F1: 0.5131
sub_26:Test (Best Model) - Loss: 1.1996 - Accuracy: 0.6029 - F1: 0.5767
sub_8:Test (Best Model) - Loss: 1.1138 - Accuracy: 0.6029 - F1: 0.6165
sub_17:Test (Best Model) - Loss: 1.1841 - Accuracy: 0.5507 - F1: 0.5131
sub_3:Test (Best Model) - Loss: 1.0758 - Accuracy: 0.7826 - F1: 0.7865
sub_10:Test (Best Model) - Loss: 1.1181 - Accuracy: 0.6812 - F1: 0.6352
sub_28:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.3971 - F1: 0.2854
sub_12:Test (Best Model) - Loss: 1.0982 - Accuracy: 0.6765 - F1: 0.6840
sub_9:Test (Best Model) - Loss: 1.1440 - Accuracy: 0.6029 - F1: 0.6061
sub_24:Test (Best Model) - Loss: 1.1605 - Accuracy: 0.7353 - F1: 0.7517
sub_14:Test (Best Model) - Loss: 1.1491 - Accuracy: 0.5882 - F1: 0.5705
sub_1:Test (Best Model) - Loss: 1.0875 - Accuracy: 0.7206 - F1: 0.6507
sub_2:Test (Best Model) - Loss: 1.2669 - Accuracy: 0.4058 - F1: 0.3173
sub_18:Test (Best Model) - Loss: 1.1442 - Accuracy: 0.6176 - F1: 0.6082
sub_23:Test (Best Model) - Loss: 1.1821 - Accuracy: 0.6087 - F1: 0.5527
sub_29:Test (Best Model) - Loss: 0.9489 - Accuracy: 0.9265 - F1: 0.9292
sub_25:Test (Best Model) - Loss: 1.0986 - Accuracy: 0.7647 - F1: 0.7664
sub_6:Test (Best Model) - Loss: 1.0525 - Accuracy: 0.6957 - F1: 0.6197
sub_15:Test (Best Model) - Loss: 1.0768 - Accuracy: 0.7794 - F1: 0.7848
sub_13:Test (Best Model) - Loss: 1.2032 - Accuracy: 0.5652 - F1: 0.5528
sub_11:Test (Best Model) - Loss: 1.1467 - Accuracy: 0.6522 - F1: 0.6420
sub_22:Test (Best Model) - Loss: 1.1718 - Accuracy: 0.7059 - F1: 0.6809
sub_16:Test (Best Model) - Loss: 1.0861 - Accuracy: 0.7647 - F1: 0.7627
sub_7:Test (Best Model) - Loss: 1.1018 - Accuracy: 0.8382 - F1: 0.8354
sub_8:Test (Best Model) - Loss: 1.1668 - Accuracy: 0.5588 - F1: 0.5678
sub_19:Test (Best Model) - Loss: 1.1691 - Accuracy: 0.5588 - F1: 0.5093
sub_5:Test (Best Model) - Loss: 1.1174 - Accuracy: 0.7353 - F1: 0.6729
sub_4:Test (Best Model) - Loss: 1.0763 - Accuracy: 0.7536 - F1: 0.7669
sub_27:Test (Best Model) - Loss: 1.0943 - Accuracy: 0.6912 - F1: 0.6335
sub_26:Test (Best Model) - Loss: 1.1158 - Accuracy: 0.6618 - F1: 0.6710
sub_20:Test (Best Model) - Loss: 0.9984 - Accuracy: 0.7536 - F1: 0.7545
sub_21:Test (Best Model) - Loss: 1.0136 - Accuracy: 0.8971 - F1: 0.8945
sub_17:Test (Best Model) - Loss: 1.0943 - Accuracy: 0.6912 - F1: 0.6335
sub_3:Test (Best Model) - Loss: 1.0988 - Accuracy: 0.7391 - F1: 0.7552
sub_10:Test (Best Model) - Loss: 1.1071 - Accuracy: 0.5942 - F1: 0.5098
sub_28:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.4706 - F1: 0.3374
sub_18:Test (Best Model) - Loss: 1.1534 - Accuracy: 0.6912 - F1: 0.6680
sub_9:Test (Best Model) - Loss: 1.1829 - Accuracy: 0.6765 - F1: 0.6825
sub_25:Test (Best Model) - Loss: 1.1368 - Accuracy: 0.6029 - F1: 0.5600
sub_14:Test (Best Model) - Loss: 1.1199 - Accuracy: 0.5882 - F1: 0.5681
sub_1:Test (Best Model) - Loss: 1.1120 - Accuracy: 0.6618 - F1: 0.6229
sub_12:Test (Best Model) - Loss: 1.1619 - Accuracy: 0.7500 - F1: 0.7614
sub_13:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.4118 - F1: 0.3047
sub_2:Test (Best Model) - Loss: 1.1798 - Accuracy: 0.5507 - F1: 0.5050
sub_23:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.5217 - F1: 0.4711
sub_24:Test (Best Model) - Loss: 1.1730 - Accuracy: 0.6029 - F1: 0.6330
sub_22:Test (Best Model) - Loss: 1.1472 - Accuracy: 0.6765 - F1: 0.6093
sub_6:Test (Best Model) - Loss: 1.1355 - Accuracy: 0.6812 - F1: 0.6274
sub_20:Test (Best Model) - Loss: 1.0909 - Accuracy: 0.6957 - F1: 0.6757
sub_11:Test (Best Model) - Loss: 1.1737 - Accuracy: 0.4928 - F1: 0.4612
sub_16:Test (Best Model) - Loss: 1.0981 - Accuracy: 0.7647 - F1: 0.7687
sub_8:Test (Best Model) - Loss: 1.1214 - Accuracy: 0.6324 - F1: 0.6015
sub_21:Test (Best Model) - Loss: 1.0990 - Accuracy: 0.7941 - F1: 0.7846
sub_19:Test (Best Model) - Loss: 1.2034 - Accuracy: 0.5882 - F1: 0.5084
sub_7:Test (Best Model) - Loss: 1.0979 - Accuracy: 0.7794 - F1: 0.7680
sub_10:Test (Best Model) - Loss: 1.1830 - Accuracy: 0.6812 - F1: 0.6109
sub_15:Test (Best Model) - Loss: 1.0297 - Accuracy: 0.7500 - F1: 0.7554
sub_3:Test (Best Model) - Loss: 1.0655 - Accuracy: 0.7246 - F1: 0.7138
sub_27:Test (Best Model) - Loss: 1.0802 - Accuracy: 0.7353 - F1: 0.7473
sub_26:Test (Best Model) - Loss: 1.1004 - Accuracy: 0.6912 - F1: 0.6955
sub_4:Test (Best Model) - Loss: 0.9984 - Accuracy: 0.6667 - F1: 0.6811
sub_17:Test (Best Model) - Loss: 1.0802 - Accuracy: 0.7353 - F1: 0.7473
sub_29:Test (Best Model) - Loss: 1.0779 - Accuracy: 0.7101 - F1: 0.6386
sub_5:Test (Best Model) - Loss: 1.1256 - Accuracy: 0.7206 - F1: 0.6393
sub_28:Test (Best Model) - Loss: 1.2927 - Accuracy: 0.4412 - F1: 0.3564
sub_2:Test (Best Model) - Loss: 1.1297 - Accuracy: 0.7101 - F1: 0.7172
sub_25:Test (Best Model) - Loss: 1.0171 - Accuracy: 0.6618 - F1: 0.6345
sub_18:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.5294 - F1: 0.4966
sub_24:Test (Best Model) - Loss: 1.1048 - Accuracy: 0.7941 - F1: 0.8063
sub_14:Test (Best Model) - Loss: 1.0408 - Accuracy: 0.8676 - F1: 0.8734
sub_1:Test (Best Model) - Loss: 1.1382 - Accuracy: 0.6029 - F1: 0.5667
sub_22:Test (Best Model) - Loss: 1.2068 - Accuracy: 0.5735 - F1: 0.5407
sub_16:Test (Best Model) - Loss: 1.0908 - Accuracy: 0.7647 - F1: 0.7661
sub_4:Test (Best Model) - Loss: 1.1140 - Accuracy: 0.6522 - F1: 0.6388
sub_7:Test (Best Model) - Loss: 1.1505 - Accuracy: 0.7059 - F1: 0.7075
sub_11:Test (Best Model) - Loss: 1.0929 - Accuracy: 0.7971 - F1: 0.7929
sub_6:Test (Best Model) - Loss: 1.0598 - Accuracy: 0.6812 - F1: 0.6239
sub_21:Test (Best Model) - Loss: 1.0679 - Accuracy: 0.7206 - F1: 0.6660
sub_12:Test (Best Model) - Loss: 1.0053 - Accuracy: 0.7059 - F1: 0.7144
sub_23:Test (Best Model) - Loss: 1.1992 - Accuracy: 0.5507 - F1: 0.5051
sub_13:Test (Best Model) - Loss: 1.2827 - Accuracy: 0.4706 - F1: 0.3554
sub_26:Test (Best Model) - Loss: 1.0970 - Accuracy: 0.6176 - F1: 0.5877
sub_20:Test (Best Model) - Loss: 0.9943 - Accuracy: 0.7681 - F1: 0.7642
sub_8:Test (Best Model) - Loss: 1.1477 - Accuracy: 0.5147 - F1: 0.5265
sub_17:Test (Best Model) - Loss: 1.1238 - Accuracy: 0.5882 - F1: 0.5753
sub_29:Test (Best Model) - Loss: 1.1238 - Accuracy: 0.7101 - F1: 0.6386
sub_15:Test (Best Model) - Loss: 1.1123 - Accuracy: 0.7353 - F1: 0.6818
sub_27:Test (Best Model) - Loss: 1.1238 - Accuracy: 0.5882 - F1: 0.5753
sub_4:Test (Best Model) - Loss: 1.1086 - Accuracy: 0.7246 - F1: 0.6513
sub_5:Test (Best Model) - Loss: 1.1426 - Accuracy: 0.6029 - F1: 0.5477
sub_2:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.5942 - F1: 0.5715
sub_25:Test (Best Model) - Loss: 1.1054 - Accuracy: 0.7794 - F1: 0.7913
sub_19:Test (Best Model) - Loss: 1.1822 - Accuracy: 0.5735 - F1: 0.5052
sub_3:Test (Best Model) - Loss: 0.9945 - Accuracy: 0.7391 - F1: 0.7506
sub_6:Test (Best Model) - Loss: 1.1495 - Accuracy: 0.7246 - F1: 0.7030
sub_9:Test (Best Model) - Loss: 1.1536 - Accuracy: 0.5441 - F1: 0.5242
sub_28:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.4265 - F1: 0.3301
sub_14:Test (Best Model) - Loss: 1.0993 - Accuracy: 0.7206 - F1: 0.6872
sub_11:Test (Best Model) - Loss: 1.0874 - Accuracy: 0.5942 - F1: 0.5792
sub_24:Test (Best Model) - Loss: 1.0776 - Accuracy: 0.7353 - F1: 0.6765
sub_22:Test (Best Model) - Loss: 1.1810 - Accuracy: 0.6618 - F1: 0.6165
sub_7:Test (Best Model) - Loss: 1.1365 - Accuracy: 0.6618 - F1: 0.6589
sub_18:Test (Best Model) - Loss: 1.1906 - Accuracy: 0.5147 - F1: 0.4489
sub_23:Test (Best Model) - Loss: 1.2070 - Accuracy: 0.5797 - F1: 0.5121
sub_13:Test (Best Model) - Loss: 1.2926 - Accuracy: 0.4412 - F1: 0.3199
sub_21:Test (Best Model) - Loss: 1.0803 - Accuracy: 0.7794 - F1: 0.7371
sub_12:Test (Best Model) - Loss: 1.1233 - Accuracy: 0.7059 - F1: 0.7176
sub_4:Test (Best Model) - Loss: 1.1127 - Accuracy: 0.7391 - F1: 0.6989
sub_1:Test (Best Model) - Loss: 0.9933 - Accuracy: 0.7206 - F1: 0.6878
sub_2:Test (Best Model) - Loss: 1.1893 - Accuracy: 0.5507 - F1: 0.5088
sub_9:Test (Best Model) - Loss: 1.2217 - Accuracy: 0.4412 - F1: 0.4197
sub_15:Test (Best Model) - Loss: 1.1802 - Accuracy: 0.5735 - F1: 0.5167
sub_26:Test (Best Model) - Loss: 1.0295 - Accuracy: 0.7500 - F1: 0.7472
sub_29:Test (Best Model) - Loss: 1.0903 - Accuracy: 0.7391 - F1: 0.7254
sub_17:Test (Best Model) - Loss: 1.1424 - Accuracy: 0.6324 - F1: 0.5767
sub_27:Test (Best Model) - Loss: 1.1424 - Accuracy: 0.6324 - F1: 0.5767
sub_5:Test (Best Model) - Loss: 1.1463 - Accuracy: 0.7059 - F1: 0.6303
sub_24:Test (Best Model) - Loss: 1.1507 - Accuracy: 0.6765 - F1: 0.6869
sub_13:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.4559 - F1: 0.3091
sub_11:Test (Best Model) - Loss: 1.0754 - Accuracy: 0.7101 - F1: 0.7132
sub_14:Test (Best Model) - Loss: 1.1474 - Accuracy: 0.7647 - F1: 0.7757
sub_18:Test (Best Model) - Loss: 1.1923 - Accuracy: 0.4853 - F1: 0.4510
sub_21:Test (Best Model) - Loss: 1.0989 - Accuracy: 0.7794 - F1: 0.7544
sub_23:Test (Best Model) - Loss: 1.2269 - Accuracy: 0.5652 - F1: 0.5156
sub_19:Test (Best Model) - Loss: 1.2106 - Accuracy: 0.5441 - F1: 0.4931
sub_3:Test (Best Model) - Loss: 1.1385 - Accuracy: 0.6812 - F1: 0.6665
sub_7:Test (Best Model) - Loss: 1.0057 - Accuracy: 0.8971 - F1: 0.8963
sub_9:Test (Best Model) - Loss: 1.1776 - Accuracy: 0.5735 - F1: 0.5607
sub_15:Test (Best Model) - Loss: 1.1684 - Accuracy: 0.5147 - F1: 0.4025
sub_1:Test (Best Model) - Loss: 1.1604 - Accuracy: 0.6912 - F1: 0.6374
sub_29:Test (Best Model) - Loss: 1.0749 - Accuracy: 0.6957 - F1: 0.6250
sub_13:Test (Best Model) - Loss: 1.3433 - Accuracy: 0.4853 - F1: 0.4046
sub_17:Test (Best Model) - Loss: 1.1180 - Accuracy: 0.6765 - F1: 0.6724
sub_21:Test (Best Model) - Loss: 0.9952 - Accuracy: 0.9118 - F1: 0.9123
sub_27:Test (Best Model) - Loss: 1.1180 - Accuracy: 0.6765 - F1: 0.6724
sub_19:Test (Best Model) - Loss: 1.2069 - Accuracy: 0.6176 - F1: 0.5960
sub_15:Test (Best Model) - Loss: 1.0994 - Accuracy: 0.6176 - F1: 0.5452
sub_29:Test (Best Model) - Loss: 1.1263 - Accuracy: 0.6522 - F1: 0.6513
sub_15:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.7059 - F1: 0.6455

=== Summary Results ===

acc: 64.68 ± 8.11
F1: 61.98 ± 9.37
acc-in: 91.05 ± 3.29
F1-in: 90.37 ± 3.65
