lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.2206 - F1: 0.2110
sub_4:Test (Best Model) - Loss: 1.6991 - Accuracy: 0.0290 - F1: 0.0286
sub_6:Test (Best Model) - Loss: 1.4174 - Accuracy: 0.2206 - F1: 0.1215
sub_18:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.0870 - F1: 0.0819
sub_20:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.2647 - F1: 0.2251
sub_13:Test (Best Model) - Loss: 1.5710 - Accuracy: 0.1912 - F1: 0.1407
sub_10:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.1912 - F1: 0.1580
sub_12:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.2647 - F1: 0.2395
sub_28:Test (Best Model) - Loss: 1.5488 - Accuracy: 0.2500 - F1: 0.2294
sub_2:Test (Best Model) - Loss: 1.2449 - Accuracy: 0.4348 - F1: 0.3795
sub_11:Test (Best Model) - Loss: 1.5347 - Accuracy: 0.1739 - F1: 0.1751
sub_17:Test (Best Model) - Loss: 1.5891 - Accuracy: 0.1449 - F1: 0.1323
sub_9:Test (Best Model) - Loss: 1.8271 - Accuracy: 0.0147 - F1: 0.0185
sub_29:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.2941 - F1: 0.2728
sub_23:Test (Best Model) - Loss: 1.0852 - Accuracy: 0.6232 - F1: 0.6021
sub_18:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.3188 - F1: 0.2699
sub_24:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2794 - F1: 0.2486
sub_15:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.1912 - F1: 0.1938
sub_27:Test (Best Model) - Loss: 1.5891 - Accuracy: 0.1449 - F1: 0.1323
sub_3:Test (Best Model) - Loss: 1.2322 - Accuracy: 0.4118 - F1: 0.4097
sub_20:Test (Best Model) - Loss: 1.4533 - Accuracy: 0.2794 - F1: 0.2174
sub_16:Test (Best Model) - Loss: 1.6799 - Accuracy: 0.1176 - F1: 0.1199
sub_5:Test (Best Model) - Loss: 1.4753 - Accuracy: 0.2500 - F1: 0.1371
sub_22:Test (Best Model) - Loss: 1.4919 - Accuracy: 0.1324 - F1: 0.1038
sub_19:Test (Best Model) - Loss: 1.4927 - Accuracy: 0.3529 - F1: 0.3195
sub_25:Test (Best Model) - Loss: 0.9869 - Accuracy: 0.6812 - F1: 0.6844
sub_8:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.3088 - F1: 0.2848
sub_7:Test (Best Model) - Loss: 1.6813 - Accuracy: 0.1029 - F1: 0.0659
sub_4:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4928 - F1: 0.4326
sub_18:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.3333 - F1: 0.2046
sub_13:Test (Best Model) - Loss: 1.2165 - Accuracy: 0.4559 - F1: 0.4133
sub_29:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.2206 - F1: 0.1940
sub_21:Test (Best Model) - Loss: 1.0321 - Accuracy: 0.6029 - F1: 0.6100
sub_6:Test (Best Model) - Loss: 1.0761 - Accuracy: 0.5588 - F1: 0.5454
sub_28:Test (Best Model) - Loss: 1.4095 - Accuracy: 0.3088 - F1: 0.2541
sub_11:Test (Best Model) - Loss: 1.2182 - Accuracy: 0.3913 - F1: 0.3583
sub_2:Test (Best Model) - Loss: 1.0880 - Accuracy: 0.5217 - F1: 0.5224
sub_14:Test (Best Model) - Loss: 1.3156 - Accuracy: 0.2059 - F1: 0.2148
sub_1:Test (Best Model) - Loss: 1.2178 - Accuracy: 0.4118 - F1: 0.3583
sub_3:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.2647 - F1: 0.1803
sub_10:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.4265 - F1: 0.4109
sub_17:Test (Best Model) - Loss: 1.0654 - Accuracy: 0.5362 - F1: 0.5264
sub_9:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.1471 - F1: 0.1566
sub_26:Test (Best Model) - Loss: 1.1119 - Accuracy: 0.4783 - F1: 0.4523
sub_27:Test (Best Model) - Loss: 1.0654 - Accuracy: 0.5362 - F1: 0.5264
sub_23:Test (Best Model) - Loss: 1.0789 - Accuracy: 0.5072 - F1: 0.4194
sub_15:Test (Best Model) - Loss: 1.2904 - Accuracy: 0.4265 - F1: 0.3462
sub_22:Test (Best Model) - Loss: 1.4734 - Accuracy: 0.3235 - F1: 0.3094
sub_18:Test (Best Model) - Loss: 1.5234 - Accuracy: 0.2464 - F1: 0.1502
sub_28:Test (Best Model) - Loss: 1.8446 - Accuracy: 0.1618 - F1: 0.1306
sub_11:Test (Best Model) - Loss: 1.6800 - Accuracy: 0.2464 - F1: 0.1868
sub_25:Test (Best Model) - Loss: 1.1898 - Accuracy: 0.4783 - F1: 0.4392
sub_14:Test (Best Model) - Loss: 1.5372 - Accuracy: 0.1912 - F1: 0.1061
sub_8:Test (Best Model) - Loss: 1.0209 - Accuracy: 0.6029 - F1: 0.5943
sub_17:Test (Best Model) - Loss: 1.5044 - Accuracy: 0.3913 - F1: 0.3375
sub_5:Test (Best Model) - Loss: 1.2833 - Accuracy: 0.5441 - F1: 0.4674
sub_12:Test (Best Model) - Loss: 1.1536 - Accuracy: 0.5588 - F1: 0.5666
sub_24:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.4118 - F1: 0.3385
sub_27:Test (Best Model) - Loss: 1.5044 - Accuracy: 0.3913 - F1: 0.3375
sub_13:Test (Best Model) - Loss: 1.4372 - Accuracy: 0.3824 - F1: 0.2500
sub_10:Test (Best Model) - Loss: 1.6363 - Accuracy: 0.1618 - F1: 0.1467
sub_7:Test (Best Model) - Loss: 1.2089 - Accuracy: 0.4706 - F1: 0.3803
sub_28:Test (Best Model) - Loss: 1.2470 - Accuracy: 0.4706 - F1: 0.3422
sub_20:Test (Best Model) - Loss: 1.2507 - Accuracy: 0.5147 - F1: 0.4381
sub_21:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.4118 - F1: 0.4191
sub_6:Test (Best Model) - Loss: 1.5310 - Accuracy: 0.1471 - F1: 0.1253
sub_12:Test (Best Model) - Loss: 1.5402 - Accuracy: 0.2059 - F1: 0.1128
sub_13:Test (Best Model) - Loss: 1.5429 - Accuracy: 0.0735 - F1: 0.0555
sub_4:Test (Best Model) - Loss: 1.2614 - Accuracy: 0.5362 - F1: 0.4824
sub_9:Test (Best Model) - Loss: 1.2406 - Accuracy: 0.3676 - F1: 0.3080
sub_29:Test (Best Model) - Loss: 1.4420 - Accuracy: 0.3088 - F1: 0.1990
sub_7:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.1471 - F1: 0.1339
sub_17:Test (Best Model) - Loss: 1.1166 - Accuracy: 0.5797 - F1: 0.4800
sub_28:Test (Best Model) - Loss: 1.6291 - Accuracy: 0.2500 - F1: 0.1247
sub_19:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2206 - F1: 0.1490
sub_10:Test (Best Model) - Loss: 1.4170 - Accuracy: 0.2941 - F1: 0.1786
sub_24:Test (Best Model) - Loss: 1.4855 - Accuracy: 0.3235 - F1: 0.2153
sub_22:Test (Best Model) - Loss: 1.5698 - Accuracy: 0.2500 - F1: 0.1062
sub_27:Test (Best Model) - Loss: 1.1166 - Accuracy: 0.5797 - F1: 0.4800
sub_8:Test (Best Model) - Loss: 1.3200 - Accuracy: 0.3235 - F1: 0.2197
sub_14:Test (Best Model) - Loss: 1.5205 - Accuracy: 0.3088 - F1: 0.2239
sub_6:Test (Best Model) - Loss: 1.4651 - Accuracy: 0.2647 - F1: 0.1340
sub_25:Test (Best Model) - Loss: 1.2570 - Accuracy: 0.4638 - F1: 0.3548
sub_12:Test (Best Model) - Loss: 1.4906 - Accuracy: 0.2500 - F1: 0.1860
sub_26:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.4638 - F1: 0.4333
sub_18:Test (Best Model) - Loss: 1.5026 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.4437 - Accuracy: 0.2754 - F1: 0.1409
sub_2:Test (Best Model) - Loss: 1.2038 - Accuracy: 0.5507 - F1: 0.4782
sub_3:Test (Best Model) - Loss: 1.4299 - Accuracy: 0.2500 - F1: 0.1202
sub_1:Test (Best Model) - Loss: 1.2830 - Accuracy: 0.4118 - F1: 0.3249
sub_13:Test (Best Model) - Loss: 1.7558 - Accuracy: 0.2500 - F1: 0.1253
sub_17:Test (Best Model) - Loss: 1.8409 - Accuracy: 0.1739 - F1: 0.0811
sub_29:Test (Best Model) - Loss: 1.4694 - Accuracy: 0.2059 - F1: 0.1849
sub_24:Test (Best Model) - Loss: 1.4214 - Accuracy: 0.2647 - F1: 0.2183
sub_10:Test (Best Model) - Loss: 1.4019 - Accuracy: 0.4265 - F1: 0.3389
sub_16:Test (Best Model) - Loss: 1.1072 - Accuracy: 0.6029 - F1: 0.5954
sub_27:Test (Best Model) - Loss: 1.8409 - Accuracy: 0.1739 - F1: 0.0811
sub_6:Test (Best Model) - Loss: 1.5948 - Accuracy: 0.2647 - F1: 0.1059
sub_12:Test (Best Model) - Loss: 1.4760 - Accuracy: 0.3529 - F1: 0.2222
sub_15:Test (Best Model) - Loss: 1.1823 - Accuracy: 0.4706 - F1: 0.4036
sub_11:Test (Best Model) - Loss: 1.5595 - Accuracy: 0.4348 - F1: 0.2857
sub_19:Test (Best Model) - Loss: 1.2783 - Accuracy: 0.4559 - F1: 0.3811
sub_1:Test (Best Model) - Loss: 1.4806 - Accuracy: 0.3235 - F1: 0.2736
sub_14:Test (Best Model) - Loss: 1.5113 - Accuracy: 0.2500 - F1: 0.1361
sub_4:Test (Best Model) - Loss: 1.5687 - Accuracy: 0.2319 - F1: 0.1961
sub_9:Test (Best Model) - Loss: 1.0940 - Accuracy: 0.5882 - F1: 0.4816
sub_20:Test (Best Model) - Loss: 1.6657 - Accuracy: 0.0882 - F1: 0.0730
sub_24:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2500 - F1: 0.1226
sub_23:Test (Best Model) - Loss: 1.2991 - Accuracy: 0.3623 - F1: 0.3171
sub_28:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.2941 - F1: 0.3113
sub_13:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.3478 - F1: 0.3240
sub_8:Test (Best Model) - Loss: 1.2765 - Accuracy: 0.2500 - F1: 0.2027
sub_25:Test (Best Model) - Loss: 1.2899 - Accuracy: 0.3768 - F1: 0.3221
sub_21:Test (Best Model) - Loss: 1.4934 - Accuracy: 0.3824 - F1: 0.3068
sub_22:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.3235 - F1: 0.2439
sub_5:Test (Best Model) - Loss: 1.1236 - Accuracy: 0.5000 - F1: 0.4495
sub_14:Test (Best Model) - Loss: 1.5201 - Accuracy: 0.4412 - F1: 0.2971
sub_10:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.4559 - F1: 0.4016
sub_1:Test (Best Model) - Loss: 1.6171 - Accuracy: 0.1618 - F1: 0.1381
sub_4:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.3478 - F1: 0.2357
sub_13:Test (Best Model) - Loss: 1.5307 - Accuracy: 0.2609 - F1: 0.1422
sub_29:Test (Best Model) - Loss: 1.4650 - Accuracy: 0.2500 - F1: 0.1202
sub_25:Test (Best Model) - Loss: 1.7181 - Accuracy: 0.2319 - F1: 0.1473
sub_18:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.3529 - F1: 0.2763
sub_26:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3913 - F1: 0.3401
sub_11:Test (Best Model) - Loss: 1.4851 - Accuracy: 0.2464 - F1: 0.2300
sub_3:Test (Best Model) - Loss: 1.5900 - Accuracy: 0.1324 - F1: 0.1284
sub_19:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.1618 - F1: 0.1059
sub_9:Test (Best Model) - Loss: 1.5785 - Accuracy: 0.2206 - F1: 0.1673
sub_21:Test (Best Model) - Loss: 1.2640 - Accuracy: 0.4853 - F1: 0.4250
sub_1:Test (Best Model) - Loss: 1.7647 - Accuracy: 0.2754 - F1: 0.1405
sub_28:Test (Best Model) - Loss: 1.4466 - Accuracy: 0.2647 - F1: 0.1111
sub_7:Test (Best Model) - Loss: 1.6548 - Accuracy: 0.2647 - F1: 0.1364
sub_29:Test (Best Model) - Loss: 1.5128 - Accuracy: 0.0588 - F1: 0.0606
sub_6:Test (Best Model) - Loss: 1.6294 - Accuracy: 0.2029 - F1: 0.1583
sub_24:Test (Best Model) - Loss: 1.6373 - Accuracy: 0.2647 - F1: 0.1331
sub_15:Test (Best Model) - Loss: 1.2425 - Accuracy: 0.4559 - F1: 0.4016
sub_17:Test (Best Model) - Loss: 1.4554 - Accuracy: 0.2609 - F1: 0.1357
sub_20:Test (Best Model) - Loss: 1.4663 - Accuracy: 0.3382 - F1: 0.2505
sub_12:Test (Best Model) - Loss: 1.5581 - Accuracy: 0.1594 - F1: 0.1477
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.4969 - Accuracy: 0.3188 - F1: 0.1925
sub_2:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3188 - F1: 0.2192
sub_27:Test (Best Model) - Loss: 1.4554 - Accuracy: 0.2609 - F1: 0.1357
sub_16:Test (Best Model) - Loss: 1.5381 - Accuracy: 0.1765 - F1: 0.1445
sub_8:Test (Best Model) - Loss: 1.6183 - Accuracy: 0.2500 - F1: 0.1076
sub_18:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.2206 - F1: 0.1523
sub_22:Test (Best Model) - Loss: 1.6724 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.5457 - Accuracy: 0.1618 - F1: 0.1058
sub_13:Test (Best Model) - Loss: 1.4817 - Accuracy: 0.2319 - F1: 0.1464
sub_4:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.2464 - F1: 0.2664
sub_23:Test (Best Model) - Loss: 1.5104 - Accuracy: 0.3188 - F1: 0.2456
sub_6:Test (Best Model) - Loss: 1.5023 - Accuracy: 0.4348 - F1: 0.2891
sub_20:Test (Best Model) - Loss: 1.5904 - Accuracy: 0.1912 - F1: 0.1981
sub_14:Test (Best Model) - Loss: 1.5871 - Accuracy: 0.2353 - F1: 0.1673
sub_2:Test (Best Model) - Loss: 1.5434 - Accuracy: 0.3188 - F1: 0.1857
sub_12:Test (Best Model) - Loss: 1.5273 - Accuracy: 0.1739 - F1: 0.1109
sub_9:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.2500 - F1: 0.2370
sub_8:Test (Best Model) - Loss: 1.6744 - Accuracy: 0.1176 - F1: 0.0849
sub_24:Test (Best Model) - Loss: 1.6490 - Accuracy: 0.2647 - F1: 0.1184
sub_3:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2647 - F1: 0.1510
sub_17:Test (Best Model) - Loss: 1.5532 - Accuracy: 0.3043 - F1: 0.1709
sub_19:Test (Best Model) - Loss: 1.6434 - Accuracy: 0.2353 - F1: 0.1039
sub_18:Test (Best Model) - Loss: 1.6285 - Accuracy: 0.0441 - F1: 0.0366
sub_28:Test (Best Model) - Loss: 1.4799 - Accuracy: 0.2794 - F1: 0.1383
sub_21:Test (Best Model) - Loss: 1.6426 - Accuracy: 0.2206 - F1: 0.1014
sub_7:Test (Best Model) - Loss: 1.4567 - Accuracy: 0.1765 - F1: 0.0857
sub_22:Test (Best Model) - Loss: 1.4226 - Accuracy: 0.2754 - F1: 0.2048
sub_10:Test (Best Model) - Loss: 1.5183 - Accuracy: 0.1765 - F1: 0.0907
sub_29:Test (Best Model) - Loss: 1.7588 - Accuracy: 0.0882 - F1: 0.0802
sub_27:Test (Best Model) - Loss: 1.5532 - Accuracy: 0.3043 - F1: 0.1709
sub_13:Test (Best Model) - Loss: 2.0223 - Accuracy: 0.2319 - F1: 0.1214
sub_4:Test (Best Model) - Loss: 1.5126 - Accuracy: 0.3188 - F1: 0.1860
sub_23:Test (Best Model) - Loss: 1.6499 - Accuracy: 0.1304 - F1: 0.0851
sub_5:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.0882 - F1: 0.0455
sub_15:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.2353 - F1: 0.1957
sub_14:Test (Best Model) - Loss: 1.5106 - Accuracy: 0.3235 - F1: 0.2020
sub_12:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3768 - F1: 0.3171
sub_1:Test (Best Model) - Loss: 1.4734 - Accuracy: 0.3043 - F1: 0.1709
sub_9:Test (Best Model) - Loss: 1.7424 - Accuracy: 0.2794 - F1: 0.1640
sub_26:Test (Best Model) - Loss: 1.3439 - Accuracy: 0.3188 - F1: 0.2851
sub_28:Test (Best Model) - Loss: 1.7149 - Accuracy: 0.3088 - F1: 0.2051
sub_11:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.4928 - F1: 0.4382
sub_2:Test (Best Model) - Loss: 1.5376 - Accuracy: 0.0441 - F1: 0.0529
sub_13:Test (Best Model) - Loss: 1.1810 - Accuracy: 0.4638 - F1: 0.3974
sub_10:Test (Best Model) - Loss: 1.5197 - Accuracy: 0.1176 - F1: 0.0799
sub_23:Test (Best Model) - Loss: 1.5384 - Accuracy: 0.2647 - F1: 0.1200
sub_5:Test (Best Model) - Loss: 1.4831 - Accuracy: 0.2647 - F1: 0.1275
sub_24:Test (Best Model) - Loss: 1.3121 - Accuracy: 0.3235 - F1: 0.3122
sub_8:Test (Best Model) - Loss: 1.7706 - Accuracy: 0.2206 - F1: 0.0938
sub_25:Test (Best Model) - Loss: 1.1619 - Accuracy: 0.4265 - F1: 0.3593
sub_20:Test (Best Model) - Loss: 1.6900 - Accuracy: 0.2647 - F1: 0.1184
sub_6:Test (Best Model) - Loss: 1.7246 - Accuracy: 0.1159 - F1: 0.0924
sub_19:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3971 - F1: 0.3522
sub_16:Test (Best Model) - Loss: 1.3939 - Accuracy: 0.3382 - F1: 0.2267
sub_17:Test (Best Model) - Loss: 1.6873 - Accuracy: 0.2029 - F1: 0.0909
sub_22:Test (Best Model) - Loss: 1.4594 - Accuracy: 0.2609 - F1: 0.1084
sub_26:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2319 - F1: 0.1399
sub_2:Test (Best Model) - Loss: 1.4993 - Accuracy: 0.2353 - F1: 0.1279
sub_29:Test (Best Model) - Loss: 1.6997 - Accuracy: 0.3235 - F1: 0.2668
sub_27:Test (Best Model) - Loss: 1.6873 - Accuracy: 0.2029 - F1: 0.0909
sub_9:Test (Best Model) - Loss: 1.7542 - Accuracy: 0.0441 - F1: 0.0306
sub_7:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2206 - F1: 0.2282
sub_23:Test (Best Model) - Loss: 1.4313 - Accuracy: 0.2500 - F1: 0.1012
sub_15:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.3235 - F1: 0.2339
sub_11:Test (Best Model) - Loss: 1.5589 - Accuracy: 0.1884 - F1: 0.1240
sub_1:Test (Best Model) - Loss: 1.5082 - Accuracy: 0.2609 - F1: 0.1268
sub_20:Test (Best Model) - Loss: 1.4835 - Accuracy: 0.2500 - F1: 0.2001
sub_25:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2206 - F1: 0.1094
sub_19:Test (Best Model) - Loss: 1.4605 - Accuracy: 0.2647 - F1: 0.1233
sub_10:Test (Best Model) - Loss: 1.3478 - Accuracy: 0.3382 - F1: 0.2467
sub_3:Test (Best Model) - Loss: 1.4161 - Accuracy: 0.4058 - F1: 0.3601
sub_16:Test (Best Model) - Loss: 1.5063 - Accuracy: 0.2794 - F1: 0.1794
sub_4:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.3478 - F1: 0.2676
sub_5:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.2647 - F1: 0.2346
sub_13:Test (Best Model) - Loss: 1.5014 - Accuracy: 0.3676 - F1: 0.2768
sub_18:Test (Best Model) - Loss: 1.5682 - Accuracy: 0.2794 - F1: 0.2051
sub_15:Test (Best Model) - Loss: 1.8571 - Accuracy: 0.2206 - F1: 0.0949
sub_23:Test (Best Model) - Loss: 1.7519 - Accuracy: 0.2647 - F1: 0.1233
sub_24:Test (Best Model) - Loss: 1.6375 - Accuracy: 0.2059 - F1: 0.2019
sub_12:Test (Best Model) - Loss: 1.4409 - Accuracy: 0.3623 - F1: 0.3254
sub_21:Test (Best Model) - Loss: 1.0691 - Accuracy: 0.6176 - F1: 0.5761
sub_8:Test (Best Model) - Loss: 1.4850 - Accuracy: 0.1765 - F1: 0.1408
sub_10:Test (Best Model) - Loss: 1.4538 - Accuracy: 0.2319 - F1: 0.1297
sub_14:Test (Best Model) - Loss: 1.3034 - Accuracy: 0.2794 - F1: 0.2089
sub_4:Test (Best Model) - Loss: 1.5325 - Accuracy: 0.3333 - F1: 0.2426
sub_3:Test (Best Model) - Loss: 1.5687 - Accuracy: 0.3188 - F1: 0.1858
sub_5:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.2794 - F1: 0.1543
sub_7:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3529 - F1: 0.2317
sub_29:Test (Best Model) - Loss: 1.6360 - Accuracy: 0.0441 - F1: 0.0455
sub_28:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.3088 - F1: 0.2803
sub_13:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.3529 - F1: 0.2693
sub_19:Test (Best Model) - Loss: 1.8109 - Accuracy: 0.1471 - F1: 0.0758
sub_18:Test (Best Model) - Loss: 1.8557 - Accuracy: 0.1618 - F1: 0.0887
sub_22:Test (Best Model) - Loss: 1.4519 - Accuracy: 0.3188 - F1: 0.2568
sub_2:Test (Best Model) - Loss: 1.5072 - Accuracy: 0.3676 - F1: 0.3026
sub_15:Test (Best Model) - Loss: 1.7849 - Accuracy: 0.1912 - F1: 0.0956
sub_1:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2754 - F1: 0.2593
sub_21:Test (Best Model) - Loss: 1.4520 - Accuracy: 0.2794 - F1: 0.1985
sub_8:Test (Best Model) - Loss: 1.7383 - Accuracy: 0.0882 - F1: 0.0743
sub_14:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.3676 - F1: 0.3323
sub_11:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.3913 - F1: 0.2861
sub_12:Test (Best Model) - Loss: 1.3100 - Accuracy: 0.4638 - F1: 0.3906
sub_3:Test (Best Model) - Loss: 1.6780 - Accuracy: 0.3188 - F1: 0.2064
sub_6:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.4638 - F1: 0.4111
sub_25:Test (Best Model) - Loss: 1.7078 - Accuracy: 0.0147 - F1: 0.0098
sub_13:Test (Best Model) - Loss: 1.6643 - Accuracy: 0.1618 - F1: 0.1133
sub_22:Test (Best Model) - Loss: 1.5314 - Accuracy: 0.2029 - F1: 0.2005
sub_23:Test (Best Model) - Loss: 1.8448 - Accuracy: 0.1324 - F1: 0.1128
sub_16:Test (Best Model) - Loss: 1.4699 - Accuracy: 0.2206 - F1: 0.2244
sub_10:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.1159 - F1: 0.0667
sub_20:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.3382 - F1: 0.3336
sub_9:Test (Best Model) - Loss: 1.4692 - Accuracy: 0.3824 - F1: 0.3244
sub_8:Test (Best Model) - Loss: 1.5042 - Accuracy: 0.3529 - F1: 0.2421
sub_4:Test (Best Model) - Loss: 1.2742 - Accuracy: 0.3623 - F1: 0.3543
sub_17:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.2029 - F1: 0.1693
sub_26:Test (Best Model) - Loss: 1.1457 - Accuracy: 0.5441 - F1: 0.5398
sub_24:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.4706 - F1: 0.3892
sub_6:Test (Best Model) - Loss: 1.4857 - Accuracy: 0.2319 - F1: 0.2002
sub_1:Test (Best Model) - Loss: 1.2343 - Accuracy: 0.4058 - F1: 0.3508
sub_19:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.1324 - F1: 0.0900
sub_22:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3913 - F1: 0.3357
sub_27:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.2029 - F1: 0.1693
sub_16:Test (Best Model) - Loss: 1.4879 - Accuracy: 0.2206 - F1: 0.1376
sub_5:Test (Best Model) - Loss: 1.5948 - Accuracy: 0.2500 - F1: 0.1181
sub_10:Test (Best Model) - Loss: 1.3148 - Accuracy: 0.2899 - F1: 0.2548
sub_29:Test (Best Model) - Loss: 1.5109 - Accuracy: 0.3043 - F1: 0.1967
sub_12:Test (Best Model) - Loss: 1.4949 - Accuracy: 0.2059 - F1: 0.1319
sub_4:Test (Best Model) - Loss: 1.5954 - Accuracy: 0.2029 - F1: 0.1842
sub_2:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2794 - F1: 0.2914
sub_25:Test (Best Model) - Loss: 1.6940 - Accuracy: 0.1029 - F1: 0.0830
sub_3:Test (Best Model) - Loss: 1.7746 - Accuracy: 0.2174 - F1: 0.1000
sub_26:Test (Best Model) - Loss: 1.4477 - Accuracy: 0.3382 - F1: 0.2300
sub_6:Test (Best Model) - Loss: 1.5440 - Accuracy: 0.3623 - F1: 0.2702
sub_18:Test (Best Model) - Loss: 1.4270 - Accuracy: 0.2500 - F1: 0.1678
sub_11:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.2754 - F1: 0.1883
sub_14:Test (Best Model) - Loss: 1.4497 - Accuracy: 0.3088 - F1: 0.2569
sub_28:Test (Best Model) - Loss: 1.6772 - Accuracy: 0.1618 - F1: 0.1317
sub_22:Test (Best Model) - Loss: 1.5746 - Accuracy: 0.3235 - F1: 0.2022
sub_20:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.4412 - F1: 0.3935
sub_1:Test (Best Model) - Loss: 1.7523 - Accuracy: 0.1324 - F1: 0.0966
sub_17:Test (Best Model) - Loss: 1.3128 - Accuracy: 0.4638 - F1: 0.3935
sub_13:Test (Best Model) - Loss: 1.4913 - Accuracy: 0.2353 - F1: 0.2127
sub_21:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3971 - F1: 0.3041
sub_27:Test (Best Model) - Loss: 1.3128 - Accuracy: 0.4638 - F1: 0.3935
sub_18:Test (Best Model) - Loss: 1.4656 - Accuracy: 0.3382 - F1: 0.2227
sub_23:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.2941 - F1: 0.2183
sub_9:Test (Best Model) - Loss: 1.4946 - Accuracy: 0.2647 - F1: 0.2486
sub_20:Test (Best Model) - Loss: 1.7751 - Accuracy: 0.2029 - F1: 0.1445
sub_15:Test (Best Model) - Loss: 1.1347 - Accuracy: 0.4853 - F1: 0.4735
sub_28:Test (Best Model) - Loss: 1.7555 - Accuracy: 0.1029 - F1: 0.0666
sub_24:Test (Best Model) - Loss: 1.5905 - Accuracy: 0.2794 - F1: 0.2188
sub_1:Test (Best Model) - Loss: 1.4575 - Accuracy: 0.2647 - F1: 0.1763
sub_17:Test (Best Model) - Loss: 1.3130 - Accuracy: 0.4412 - F1: 0.3439
sub_16:Test (Best Model) - Loss: 1.4763 - Accuracy: 0.3235 - F1: 0.2031
sub_19:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3971 - F1: 0.3240
sub_10:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.4928 - F1: 0.4299
sub_7:Test (Best Model) - Loss: 1.2237 - Accuracy: 0.3971 - F1: 0.3034
sub_13:Test (Best Model) - Loss: 1.4532 - Accuracy: 0.1912 - F1: 0.1463
sub_27:Test (Best Model) - Loss: 1.3130 - Accuracy: 0.4412 - F1: 0.3439
sub_25:Test (Best Model) - Loss: 1.2659 - Accuracy: 0.4118 - F1: 0.3688
sub_3:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.3188 - F1: 0.2741
sub_5:Test (Best Model) - Loss: 1.4671 - Accuracy: 0.3824 - F1: 0.3368
sub_15:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.3382 - F1: 0.3092
sub_9:Test (Best Model) - Loss: 1.4648 - Accuracy: 0.2941 - F1: 0.2147
sub_12:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.1912 - F1: 0.1230
sub_4:Test (Best Model) - Loss: 1.6581 - Accuracy: 0.2029 - F1: 0.1533
sub_6:Test (Best Model) - Loss: 1.6594 - Accuracy: 0.3188 - F1: 0.2190
sub_2:Test (Best Model) - Loss: 1.5247 - Accuracy: 0.2794 - F1: 0.2512
sub_8:Test (Best Model) - Loss: 1.4283 - Accuracy: 0.3088 - F1: 0.3352
sub_26:Test (Best Model) - Loss: 1.6557 - Accuracy: 0.2353 - F1: 0.1397
sub_11:Test (Best Model) - Loss: 1.4523 - Accuracy: 0.3188 - F1: 0.2611
sub_19:Test (Best Model) - Loss: 1.4163 - Accuracy: 0.4265 - F1: 0.3604
sub_7:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.1471 - F1: 0.1169
sub_16:Test (Best Model) - Loss: 1.5788 - Accuracy: 0.1324 - F1: 0.1554
sub_21:Test (Best Model) - Loss: 1.3273 - Accuracy: 0.3529 - F1: 0.2828
sub_14:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.4265 - F1: 0.3314
sub_3:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.4203 - F1: 0.3328
sub_22:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.3088 - F1: 0.1773
sub_1:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2353 - F1: 0.1375
sub_12:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.2794 - F1: 0.2030
sub_28:Test (Best Model) - Loss: 1.5080 - Accuracy: 0.2206 - F1: 0.1167
sub_29:Test (Best Model) - Loss: 1.4855 - Accuracy: 0.1449 - F1: 0.1142
sub_10:Test (Best Model) - Loss: 1.3083 - Accuracy: 0.3478 - F1: 0.3087
sub_25:Test (Best Model) - Loss: 1.8618 - Accuracy: 0.0588 - F1: 0.0531
sub_20:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.1304 - F1: 0.0786
sub_7:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.3971 - F1: 0.3410
sub_23:Test (Best Model) - Loss: 1.6335 - Accuracy: 0.1884 - F1: 0.1068
sub_9:Test (Best Model) - Loss: 1.6897 - Accuracy: 0.2206 - F1: 0.1087
sub_18:Test (Best Model) - Loss: 1.5746 - Accuracy: 0.2941 - F1: 0.1970
sub_16:Test (Best Model) - Loss: 1.6392 - Accuracy: 0.1912 - F1: 0.2083
sub_24:Test (Best Model) - Loss: 1.5688 - Accuracy: 0.2941 - F1: 0.2139
sub_5:Test (Best Model) - Loss: 1.4366 - Accuracy: 0.3971 - F1: 0.3247
sub_26:Test (Best Model) - Loss: 1.7260 - Accuracy: 0.2500 - F1: 0.2009
sub_4:Test (Best Model) - Loss: 1.7953 - Accuracy: 0.2609 - F1: 0.1553
sub_1:Test (Best Model) - Loss: 1.3636 - Accuracy: 0.3529 - F1: 0.3404
sub_17:Test (Best Model) - Loss: 1.5224 - Accuracy: 0.2500 - F1: 0.1643
sub_29:Test (Best Model) - Loss: 2.0178 - Accuracy: 0.2609 - F1: 0.1735
sub_20:Test (Best Model) - Loss: 1.4846 - Accuracy: 0.2609 - F1: 0.1979
sub_19:Test (Best Model) - Loss: 1.4935 - Accuracy: 0.1765 - F1: 0.1139
sub_6:Test (Best Model) - Loss: 1.8500 - Accuracy: 0.2029 - F1: 0.0921
sub_27:Test (Best Model) - Loss: 1.5224 - Accuracy: 0.2500 - F1: 0.1643
sub_21:Test (Best Model) - Loss: 1.3066 - Accuracy: 0.2794 - F1: 0.2248
sub_3:Test (Best Model) - Loss: 1.5136 - Accuracy: 0.2609 - F1: 0.1873
sub_9:Test (Best Model) - Loss: 1.4700 - Accuracy: 0.1618 - F1: 0.0733
sub_26:Test (Best Model) - Loss: 1.5770 - Accuracy: 0.0882 - F1: 0.0566
sub_1:Test (Best Model) - Loss: 1.4730 - Accuracy: 0.1765 - F1: 0.1663
sub_17:Test (Best Model) - Loss: 1.5364 - Accuracy: 0.2206 - F1: 0.1290
sub_7:Test (Best Model) - Loss: 1.2217 - Accuracy: 0.4853 - F1: 0.3764
sub_2:Test (Best Model) - Loss: 1.2133 - Accuracy: 0.4783 - F1: 0.3655
sub_12:Test (Best Model) - Loss: 1.2320 - Accuracy: 0.3529 - F1: 0.3514
sub_11:Test (Best Model) - Loss: 1.4984 - Accuracy: 0.3768 - F1: 0.2718
sub_28:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.4706 - F1: 0.4843
sub_8:Test (Best Model) - Loss: 1.7202 - Accuracy: 0.2500 - F1: 0.1746
sub_27:Test (Best Model) - Loss: 1.5364 - Accuracy: 0.2206 - F1: 0.1290
sub_16:Test (Best Model) - Loss: 1.1342 - Accuracy: 0.6471 - F1: 0.5461
sub_18:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.1618 - F1: 0.1511
sub_4:Test (Best Model) - Loss: 1.1126 - Accuracy: 0.5072 - F1: 0.5064
sub_22:Test (Best Model) - Loss: 1.8496 - Accuracy: 0.1765 - F1: 0.1017
sub_26:Test (Best Model) - Loss: 1.6479 - Accuracy: 0.2941 - F1: 0.2036
sub_14:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2647 - F1: 0.1059
sub_3:Test (Best Model) - Loss: 1.5314 - Accuracy: 0.2609 - F1: 0.2168
sub_15:Test (Best Model) - Loss: 1.4746 - Accuracy: 0.3382 - F1: 0.2726
sub_23:Test (Best Model) - Loss: 1.5311 - Accuracy: 0.1159 - F1: 0.0848
sub_19:Test (Best Model) - Loss: 1.5630 - Accuracy: 0.2353 - F1: 0.1661
sub_29:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.3478 - F1: 0.2459
sub_24:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.1471 - F1: 0.1309
sub_18:Test (Best Model) - Loss: 1.5546 - Accuracy: 0.2941 - F1: 0.1612
sub_4:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.2609 - F1: 0.2002
sub_20:Test (Best Model) - Loss: 1.1397 - Accuracy: 0.4638 - F1: 0.4280
sub_28:Test (Best Model) - Loss: 1.5734 - Accuracy: 0.2794 - F1: 0.1431
sub_8:Test (Best Model) - Loss: 1.8964 - Accuracy: 0.1471 - F1: 0.0714
sub_6:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.4058 - F1: 0.3631
sub_9:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.5147 - F1: 0.4746
sub_14:Test (Best Model) - Loss: 1.8097 - Accuracy: 0.0294 - F1: 0.0256
sub_16:Test (Best Model) - Loss: 1.6717 - Accuracy: 0.1912 - F1: 0.1433
sub_17:Test (Best Model) - Loss: 1.4149 - Accuracy: 0.3971 - F1: 0.3589
sub_2:Test (Best Model) - Loss: 1.5739 - Accuracy: 0.2464 - F1: 0.1049
sub_25:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.2647 - F1: 0.2647
sub_15:Test (Best Model) - Loss: 1.4935 - Accuracy: 0.2059 - F1: 0.1339
sub_21:Test (Best Model) - Loss: 1.0343 - Accuracy: 0.6029 - F1: 0.5134
sub_11:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3333 - F1: 0.2898
sub_7:Test (Best Model) - Loss: 1.5887 - Accuracy: 0.2647 - F1: 0.1125
sub_27:Test (Best Model) - Loss: 1.4149 - Accuracy: 0.3971 - F1: 0.3589
sub_20:Test (Best Model) - Loss: 1.5066 - Accuracy: 0.1739 - F1: 0.1510
sub_12:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.2941 - F1: 0.2524
sub_16:Test (Best Model) - Loss: 1.4342 - Accuracy: 0.3529 - F1: 0.2630
sub_26:Test (Best Model) - Loss: 1.3271 - Accuracy: 0.2647 - F1: 0.2083
sub_2:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.3188 - F1: 0.2702
sub_25:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.3676 - F1: 0.2838
sub_5:Test (Best Model) - Loss: 1.2615 - Accuracy: 0.5000 - F1: 0.4642
sub_15:Test (Best Model) - Loss: 1.5653 - Accuracy: 0.2206 - F1: 0.1732
sub_22:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.3235 - F1: 0.3160
sub_19:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.3529 - F1: 0.3341
sub_24:Test (Best Model) - Loss: 1.4946 - Accuracy: 0.1029 - F1: 0.1039
sub_6:Test (Best Model) - Loss: 1.2409 - Accuracy: 0.5072 - F1: 0.4321
sub_2:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.1884 - F1: 0.1454
sub_14:Test (Best Model) - Loss: 1.4347 - Accuracy: 0.2500 - F1: 0.1566
sub_17:Test (Best Model) - Loss: 1.2471 - Accuracy: 0.3235 - F1: 0.3352
sub_29:Test (Best Model) - Loss: 1.4244 - Accuracy: 0.2899 - F1: 0.2833
sub_15:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.2353 - F1: 0.2388
sub_16:Test (Best Model) - Loss: 1.4350 - Accuracy: 0.3382 - F1: 0.2583
sub_19:Test (Best Model) - Loss: 1.6235 - Accuracy: 0.1618 - F1: 0.1485
sub_3:Test (Best Model) - Loss: 1.1551 - Accuracy: 0.5362 - F1: 0.5111
sub_21:Test (Best Model) - Loss: 1.5045 - Accuracy: 0.2059 - F1: 0.1668
sub_27:Test (Best Model) - Loss: 1.2471 - Accuracy: 0.3235 - F1: 0.3352
sub_2:Test (Best Model) - Loss: 1.4179 - Accuracy: 0.2464 - F1: 0.2340
sub_7:Test (Best Model) - Loss: 1.7272 - Accuracy: 0.1765 - F1: 0.1095
sub_14:Test (Best Model) - Loss: 1.5294 - Accuracy: 0.2794 - F1: 0.1714
sub_26:Test (Best Model) - Loss: 1.6316 - Accuracy: 0.1471 - F1: 0.1010
sub_8:Test (Best Model) - Loss: 1.3215 - Accuracy: 0.3235 - F1: 0.2541
sub_22:Test (Best Model) - Loss: 1.4440 - Accuracy: 0.1471 - F1: 0.1318
sub_24:Test (Best Model) - Loss: 1.5319 - Accuracy: 0.2206 - F1: 0.2144
sub_9:Test (Best Model) - Loss: 1.2451 - Accuracy: 0.3676 - F1: 0.2696
sub_16:Test (Best Model) - Loss: 1.4759 - Accuracy: 0.3529 - F1: 0.2712
sub_23:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.5072 - F1: 0.4699
sub_11:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.3333 - F1: 0.2602
sub_3:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2174 - F1: 0.2412
sub_5:Test (Best Model) - Loss: 1.6243 - Accuracy: 0.2941 - F1: 0.1736
sub_15:Test (Best Model) - Loss: 1.4639 - Accuracy: 0.1176 - F1: 0.1230
sub_26:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.3971 - F1: 0.3942
sub_21:Test (Best Model) - Loss: 1.6781 - Accuracy: 0.0588 - F1: 0.0535
sub_25:Test (Best Model) - Loss: 0.9763 - Accuracy: 0.6618 - F1: 0.6391
sub_8:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.3529 - F1: 0.2907
sub_5:Test (Best Model) - Loss: 1.6901 - Accuracy: 0.1324 - F1: 0.0584
sub_7:Test (Best Model) - Loss: 1.1847 - Accuracy: 0.5588 - F1: 0.5393
sub_26:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.1618 - F1: 0.1364
sub_21:Test (Best Model) - Loss: 1.2386 - Accuracy: 0.5441 - F1: 0.5120
sub_23:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.4058 - F1: 0.3313
sub_25:Test (Best Model) - Loss: 1.5188 - Accuracy: 0.1471 - F1: 0.1408
sub_21:Test (Best Model) - Loss: 1.4774 - Accuracy: 0.2353 - F1: 0.2297
sub_5:Test (Best Model) - Loss: 1.2518 - Accuracy: 0.3824 - F1: 0.2940
sub_7:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.3235 - F1: 0.2189
sub_5:Test (Best Model) - Loss: 1.8562 - Accuracy: 0.0735 - F1: 0.0906
sub_23:Test (Best Model) - Loss: 1.5527 - Accuracy: 0.2754 - F1: 0.2297

=== Summary Results ===

acc: 29.51 ± 2.93
F1: 23.17 ± 3.25
acc-in: 41.18 ± 5.18
F1-in: 35.67 ± 5.33
