lr: 0.001
sub_17:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.8696 - F1: 0.8726
sub_19:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.3235 - F1: 0.2591
sub_5:Test (Best Model) - Loss: 0.9723 - Accuracy: 0.7206 - F1: 0.6565
sub_4:Test (Best Model) - Loss: 0.8627 - Accuracy: 0.6812 - F1: 0.6387
sub_21:Test (Best Model) - Loss: 0.7313 - Accuracy: 0.8088 - F1: 0.8049
sub_24:Test (Best Model) - Loss: 0.9759 - Accuracy: 0.6176 - F1: 0.6038
sub_23:Test (Best Model) - Loss: 0.8287 - Accuracy: 0.6812 - F1: 0.6663
sub_25:Test (Best Model) - Loss: 0.3834 - Accuracy: 0.9420 - F1: 0.9384
sub_8:Test (Best Model) - Loss: 1.2035 - Accuracy: 0.5882 - F1: 0.5590
sub_6:Test (Best Model) - Loss: 1.1834 - Accuracy: 0.4118 - F1: 0.3427
sub_18:Test (Best Model) - Loss: 0.7635 - Accuracy: 0.7681 - F1: 0.7691
sub_12:Test (Best Model) - Loss: 0.9700 - Accuracy: 0.6176 - F1: 0.6139
sub_10:Test (Best Model) - Loss: 1.2419 - Accuracy: 0.4706 - F1: 0.5192
sub_29:Test (Best Model) - Loss: 0.9331 - Accuracy: 0.5882 - F1: 0.6239
sub_22:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.4118 - F1: 0.4125
sub_7:Test (Best Model) - Loss: 0.3805 - Accuracy: 0.9265 - F1: 0.9179
sub_27:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.8696 - F1: 0.8726
sub_28:Test (Best Model) - Loss: 1.0356 - Accuracy: 0.6618 - F1: 0.5837
sub_13:Test (Best Model) - Loss: 1.1714 - Accuracy: 0.5147 - F1: 0.4485
sub_3:Test (Best Model) - Loss: 1.0058 - Accuracy: 0.6471 - F1: 0.5860
sub_11:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.7391 - F1: 0.7199
sub_9:Test (Best Model) - Loss: 0.8852 - Accuracy: 0.6471 - F1: 0.6706
sub_16:Test (Best Model) - Loss: 0.7581 - Accuracy: 0.7353 - F1: 0.7410
sub_14:Test (Best Model) - Loss: 1.2295 - Accuracy: 0.4853 - F1: 0.4031
sub_17:Test (Best Model) - Loss: 0.5903 - Accuracy: 0.8841 - F1: 0.8864
sub_2:Test (Best Model) - Loss: 0.8032 - Accuracy: 0.6667 - F1: 0.6502
sub_26:Test (Best Model) - Loss: 0.8905 - Accuracy: 0.6232 - F1: 0.6431
sub_8:Test (Best Model) - Loss: 1.2167 - Accuracy: 0.5294 - F1: 0.5046
sub_25:Test (Best Model) - Loss: 0.5913 - Accuracy: 0.9710 - F1: 0.9711
sub_20:Test (Best Model) - Loss: 0.9148 - Accuracy: 0.7206 - F1: 0.6698
sub_5:Test (Best Model) - Loss: 1.0194 - Accuracy: 0.7059 - F1: 0.6460
sub_1:Test (Best Model) - Loss: 0.9723 - Accuracy: 0.5882 - F1: 0.5843
sub_19:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.3824 - F1: 0.3242
sub_4:Test (Best Model) - Loss: 0.8608 - Accuracy: 0.6957 - F1: 0.6471
sub_23:Test (Best Model) - Loss: 0.7565 - Accuracy: 0.7536 - F1: 0.7500
sub_15:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.7353 - F1: 0.7487
sub_21:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.8088 - F1: 0.7933
sub_29:Test (Best Model) - Loss: 0.9482 - Accuracy: 0.5588 - F1: 0.5593
sub_22:Test (Best Model) - Loss: 1.2101 - Accuracy: 0.5441 - F1: 0.4946
sub_9:Test (Best Model) - Loss: 0.9628 - Accuracy: 0.6029 - F1: 0.5941
sub_6:Test (Best Model) - Loss: 1.1347 - Accuracy: 0.4559 - F1: 0.4027
sub_11:Test (Best Model) - Loss: 0.8417 - Accuracy: 0.7971 - F1: 0.7930
sub_12:Test (Best Model) - Loss: 1.1361 - Accuracy: 0.6029 - F1: 0.5626
sub_10:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.4265 - F1: 0.4578
sub_24:Test (Best Model) - Loss: 0.9303 - Accuracy: 0.6324 - F1: 0.6194
sub_7:Test (Best Model) - Loss: 0.5379 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.7971 - F1: 0.8083
sub_27:Test (Best Model) - Loss: 0.5903 - Accuracy: 0.8841 - F1: 0.8864
sub_3:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.7941 - F1: 0.7929
sub_8:Test (Best Model) - Loss: 1.2230 - Accuracy: 0.5441 - F1: 0.5193
sub_17:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.8406 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 0.9216 - Accuracy: 0.7353 - F1: 0.6667
sub_16:Test (Best Model) - Loss: 0.7932 - Accuracy: 0.7059 - F1: 0.7074
sub_28:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.6176 - F1: 0.5633
sub_14:Test (Best Model) - Loss: 1.3134 - Accuracy: 0.4559 - F1: 0.3657
sub_26:Test (Best Model) - Loss: 0.8568 - Accuracy: 0.6377 - F1: 0.6449
sub_13:Test (Best Model) - Loss: 1.1473 - Accuracy: 0.5294 - F1: 0.4817
sub_15:Test (Best Model) - Loss: 0.8234 - Accuracy: 0.6618 - F1: 0.6707
sub_20:Test (Best Model) - Loss: 0.8573 - Accuracy: 0.7206 - F1: 0.6700
sub_29:Test (Best Model) - Loss: 0.9300 - Accuracy: 0.5735 - F1: 0.6088
sub_1:Test (Best Model) - Loss: 0.9908 - Accuracy: 0.5441 - F1: 0.5254
sub_11:Test (Best Model) - Loss: 0.8818 - Accuracy: 0.6667 - F1: 0.6174
sub_2:Test (Best Model) - Loss: 0.9939 - Accuracy: 0.6667 - F1: 0.6098
sub_23:Test (Best Model) - Loss: 0.8328 - Accuracy: 0.7246 - F1: 0.6565
sub_4:Test (Best Model) - Loss: 0.9444 - Accuracy: 0.6812 - F1: 0.6415
sub_19:Test (Best Model) - Loss: 1.7853 - Accuracy: 0.3382 - F1: 0.3177
sub_9:Test (Best Model) - Loss: 0.9717 - Accuracy: 0.6471 - F1: 0.6381
sub_21:Test (Best Model) - Loss: 0.7190 - Accuracy: 0.7794 - F1: 0.7738
sub_25:Test (Best Model) - Loss: 0.6271 - Accuracy: 0.9275 - F1: 0.9277
sub_7:Test (Best Model) - Loss: 0.5491 - Accuracy: 0.9412 - F1: 0.9333
sub_5:Test (Best Model) - Loss: 1.0446 - Accuracy: 0.7353 - F1: 0.6667
sub_3:Test (Best Model) - Loss: 0.8118 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.4265 - F1: 0.3524
sub_22:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.5147 - F1: 0.4626
sub_16:Test (Best Model) - Loss: 0.9113 - Accuracy: 0.6471 - F1: 0.6221
sub_12:Test (Best Model) - Loss: 1.0421 - Accuracy: 0.5441 - F1: 0.5158
sub_8:Test (Best Model) - Loss: 1.1282 - Accuracy: 0.5735 - F1: 0.5547
sub_18:Test (Best Model) - Loss: 0.7592 - Accuracy: 0.7681 - F1: 0.7696
sub_24:Test (Best Model) - Loss: 0.9461 - Accuracy: 0.6324 - F1: 0.6389
sub_10:Test (Best Model) - Loss: 1.3261 - Accuracy: 0.4412 - F1: 0.4724
sub_1:Test (Best Model) - Loss: 0.9368 - Accuracy: 0.5882 - F1: 0.5699
sub_27:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.8406 - F1: 0.8425
sub_14:Test (Best Model) - Loss: 1.4204 - Accuracy: 0.4706 - F1: 0.3929
sub_17:Test (Best Model) - Loss: 0.4496 - Accuracy: 0.9130 - F1: 0.9157
sub_28:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.6765 - F1: 0.6039
sub_29:Test (Best Model) - Loss: 0.7912 - Accuracy: 0.6324 - F1: 0.6557
sub_13:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.5882 - F1: 0.5411
sub_20:Test (Best Model) - Loss: 0.9205 - Accuracy: 0.6765 - F1: 0.6150
sub_2:Test (Best Model) - Loss: 1.0351 - Accuracy: 0.5072 - F1: 0.4618
sub_4:Test (Best Model) - Loss: 0.8496 - Accuracy: 0.6667 - F1: 0.6243
sub_11:Test (Best Model) - Loss: 0.8624 - Accuracy: 0.7391 - F1: 0.7221
sub_5:Test (Best Model) - Loss: 1.0098 - Accuracy: 0.5882 - F1: 0.5445
sub_25:Test (Best Model) - Loss: 0.5730 - Accuracy: 0.9565 - F1: 0.9523
sub_15:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.7059 - F1: 0.7143
sub_10:Test (Best Model) - Loss: 1.3114 - Accuracy: 0.4118 - F1: 0.4709
sub_19:Test (Best Model) - Loss: 1.5954 - Accuracy: 0.3824 - F1: 0.3363
sub_16:Test (Best Model) - Loss: 0.7491 - Accuracy: 0.6618 - F1: 0.6701
sub_18:Test (Best Model) - Loss: 0.8786 - Accuracy: 0.6522 - F1: 0.6729
sub_21:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.8235 - F1: 0.8165
sub_7:Test (Best Model) - Loss: 0.4696 - Accuracy: 0.9706 - F1: 0.9676
sub_3:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.8088 - F1: 0.8101
sub_26:Test (Best Model) - Loss: 0.9111 - Accuracy: 0.6812 - F1: 0.7001
sub_12:Test (Best Model) - Loss: 1.0290 - Accuracy: 0.5735 - F1: 0.5415
sub_22:Test (Best Model) - Loss: 1.2440 - Accuracy: 0.5441 - F1: 0.5126
sub_23:Test (Best Model) - Loss: 0.9440 - Accuracy: 0.7101 - F1: 0.6479
sub_9:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.7500 - F1: 0.7374
sub_24:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.6029 - F1: 0.5865
sub_8:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.5735 - F1: 0.5443
sub_20:Test (Best Model) - Loss: 0.8844 - Accuracy: 0.6618 - F1: 0.6022
sub_17:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.7971 - F1: 0.7988
sub_1:Test (Best Model) - Loss: 0.9860 - Accuracy: 0.5588 - F1: 0.5496
sub_6:Test (Best Model) - Loss: 1.1898 - Accuracy: 0.4412 - F1: 0.3885
sub_21:Test (Best Model) - Loss: 0.8976 - Accuracy: 0.7500 - F1: 0.7560
sub_28:Test (Best Model) - Loss: 1.1996 - Accuracy: 0.6765 - F1: 0.6239
sub_14:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.4706 - F1: 0.3786
sub_29:Test (Best Model) - Loss: 0.9918 - Accuracy: 0.5882 - F1: 0.5813
sub_13:Test (Best Model) - Loss: 1.1346 - Accuracy: 0.5735 - F1: 0.5250
sub_4:Test (Best Model) - Loss: 0.9100 - Accuracy: 0.6522 - F1: 0.6151
sub_11:Test (Best Model) - Loss: 0.7778 - Accuracy: 0.7246 - F1: 0.7042
sub_18:Test (Best Model) - Loss: 0.7450 - Accuracy: 0.7536 - F1: 0.7675
sub_25:Test (Best Model) - Loss: 0.4679 - Accuracy: 0.9420 - F1: 0.9411
sub_10:Test (Best Model) - Loss: 1.1334 - Accuracy: 0.5147 - F1: 0.5437
sub_16:Test (Best Model) - Loss: 0.6139 - Accuracy: 0.8529 - F1: 0.8593
sub_15:Test (Best Model) - Loss: 0.8288 - Accuracy: 0.6029 - F1: 0.6037
sub_27:Test (Best Model) - Loss: 0.4496 - Accuracy: 0.9130 - F1: 0.9157
sub_3:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.7353 - F1: 0.7158
sub_2:Test (Best Model) - Loss: 1.0442 - Accuracy: 0.5507 - F1: 0.5121
sub_5:Test (Best Model) - Loss: 0.8412 - Accuracy: 0.7206 - F1: 0.6528
sub_7:Test (Best Model) - Loss: 0.2904 - Accuracy: 0.9412 - F1: 0.9333
sub_19:Test (Best Model) - Loss: 1.4848 - Accuracy: 0.2941 - F1: 0.2545
sub_26:Test (Best Model) - Loss: 0.8570 - Accuracy: 0.6667 - F1: 0.6835
sub_22:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.4559 - F1: 0.4077
sub_23:Test (Best Model) - Loss: 0.8999 - Accuracy: 0.7101 - F1: 0.6460
sub_12:Test (Best Model) - Loss: 0.9858 - Accuracy: 0.6765 - F1: 0.6179
sub_24:Test (Best Model) - Loss: 0.9413 - Accuracy: 0.5735 - F1: 0.5463
sub_6:Test (Best Model) - Loss: 1.1139 - Accuracy: 0.5588 - F1: 0.5097
sub_25:Test (Best Model) - Loss: 0.7249 - Accuracy: 0.7794 - F1: 0.7712
sub_14:Test (Best Model) - Loss: 1.3984 - Accuracy: 0.4412 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 1.0658 - Accuracy: 0.5294 - F1: 0.5145
sub_20:Test (Best Model) - Loss: 1.0106 - Accuracy: 0.6471 - F1: 0.5866
sub_21:Test (Best Model) - Loss: 0.5013 - Accuracy: 0.8676 - F1: 0.8667
sub_17:Test (Best Model) - Loss: 1.0327 - Accuracy: 0.5362 - F1: 0.4616
sub_18:Test (Best Model) - Loss: 0.9432 - Accuracy: 0.6029 - F1: 0.6233
sub_13:Test (Best Model) - Loss: 1.2183 - Accuracy: 0.4706 - F1: 0.4129
sub_15:Test (Best Model) - Loss: 0.8118 - Accuracy: 0.7206 - F1: 0.7300
sub_10:Test (Best Model) - Loss: 0.9884 - Accuracy: 0.5588 - F1: 0.5595
sub_29:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.9118 - F1: 0.9156
sub_11:Test (Best Model) - Loss: 0.7759 - Accuracy: 0.7101 - F1: 0.6605
sub_7:Test (Best Model) - Loss: 0.8861 - Accuracy: 0.7353 - F1: 0.6631
sub_5:Test (Best Model) - Loss: 0.9235 - Accuracy: 0.7059 - F1: 0.6460
sub_8:Test (Best Model) - Loss: 0.8702 - Accuracy: 0.6912 - F1: 0.6373
sub_28:Test (Best Model) - Loss: 1.2322 - Accuracy: 0.5294 - F1: 0.4501
sub_9:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.6471 - F1: 0.6360
sub_27:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.7971 - F1: 0.7988
sub_16:Test (Best Model) - Loss: 0.8446 - Accuracy: 0.7059 - F1: 0.6605
sub_26:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.7971 - F1: 0.7989
sub_4:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.8261 - F1: 0.8097
sub_25:Test (Best Model) - Loss: 0.7862 - Accuracy: 0.7500 - F1: 0.7165
sub_3:Test (Best Model) - Loss: 0.9675 - Accuracy: 0.6377 - F1: 0.6143
sub_22:Test (Best Model) - Loss: 1.2136 - Accuracy: 0.5072 - F1: 0.4578
sub_17:Test (Best Model) - Loss: 1.1681 - Accuracy: 0.5072 - F1: 0.4243
sub_23:Test (Best Model) - Loss: 1.0469 - Accuracy: 0.6029 - F1: 0.5289
sub_6:Test (Best Model) - Loss: 1.0944 - Accuracy: 0.4638 - F1: 0.3899
sub_2:Test (Best Model) - Loss: 0.8557 - Accuracy: 0.6957 - F1: 0.6693
sub_24:Test (Best Model) - Loss: 0.9325 - Accuracy: 0.6912 - F1: 0.6074
sub_12:Test (Best Model) - Loss: 0.5669 - Accuracy: 0.7971 - F1: 0.8086
sub_14:Test (Best Model) - Loss: 0.9736 - Accuracy: 0.5441 - F1: 0.5922
sub_15:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.8529 - F1: 0.8537
sub_1:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.6667 - F1: 0.6701
sub_5:Test (Best Model) - Loss: 0.8182 - Accuracy: 0.7059 - F1: 0.6460
sub_18:Test (Best Model) - Loss: 0.8630 - Accuracy: 0.6324 - F1: 0.6484
sub_7:Test (Best Model) - Loss: 0.9676 - Accuracy: 0.7206 - F1: 0.6422
sub_8:Test (Best Model) - Loss: 0.9348 - Accuracy: 0.7206 - F1: 0.6528
sub_11:Test (Best Model) - Loss: 0.8226 - Accuracy: 0.7246 - F1: 0.6729
sub_10:Test (Best Model) - Loss: 1.0346 - Accuracy: 0.5147 - F1: 0.4696
sub_21:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.8235 - F1: 0.8165
sub_29:Test (Best Model) - Loss: 0.4673 - Accuracy: 0.9706 - F1: 0.9721
sub_19:Test (Best Model) - Loss: 1.1104 - Accuracy: 0.6029 - F1: 0.5744
sub_4:Test (Best Model) - Loss: 0.6284 - Accuracy: 0.8261 - F1: 0.8160
sub_20:Test (Best Model) - Loss: 0.7966 - Accuracy: 0.7206 - F1: 0.6502
sub_3:Test (Best Model) - Loss: 1.0675 - Accuracy: 0.6812 - F1: 0.6442
sub_22:Test (Best Model) - Loss: 1.0632 - Accuracy: 0.5507 - F1: 0.5494
sub_16:Test (Best Model) - Loss: 0.7555 - Accuracy: 0.7500 - F1: 0.7319
sub_17:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.5652 - F1: 0.5076
sub_27:Test (Best Model) - Loss: 1.0327 - Accuracy: 0.5362 - F1: 0.4616
sub_13:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.4928 - F1: 0.4869
sub_9:Test (Best Model) - Loss: 0.8037 - Accuracy: 0.6618 - F1: 0.5953
sub_28:Test (Best Model) - Loss: 1.5855 - Accuracy: 0.4265 - F1: 0.3568
sub_23:Test (Best Model) - Loss: 1.1629 - Accuracy: 0.4559 - F1: 0.3874
sub_25:Test (Best Model) - Loss: 0.7625 - Accuracy: 0.7500 - F1: 0.7240
sub_14:Test (Best Model) - Loss: 1.1352 - Accuracy: 0.4265 - F1: 0.4448
sub_2:Test (Best Model) - Loss: 0.8439 - Accuracy: 0.7059 - F1: 0.6435
sub_5:Test (Best Model) - Loss: 0.7657 - Accuracy: 0.7353 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.8261 - F1: 0.8302
sub_8:Test (Best Model) - Loss: 0.9317 - Accuracy: 0.7059 - F1: 0.6452
sub_26:Test (Best Model) - Loss: 1.1576 - Accuracy: 0.4265 - F1: 0.3941
sub_6:Test (Best Model) - Loss: 1.1369 - Accuracy: 0.5072 - F1: 0.4150
sub_10:Test (Best Model) - Loss: 1.1526 - Accuracy: 0.4118 - F1: 0.3967
sub_18:Test (Best Model) - Loss: 1.0254 - Accuracy: 0.5588 - F1: 0.5928
sub_19:Test (Best Model) - Loss: 0.8480 - Accuracy: 0.6618 - F1: 0.6620
sub_11:Test (Best Model) - Loss: 0.7902 - Accuracy: 0.7681 - F1: 0.7370
sub_15:Test (Best Model) - Loss: 0.5878 - Accuracy: 0.7941 - F1: 0.7943
sub_1:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.6812 - F1: 0.6840
sub_27:Test (Best Model) - Loss: 1.1681 - Accuracy: 0.5072 - F1: 0.4243
sub_13:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.5362 - F1: 0.5175
sub_20:Test (Best Model) - Loss: 0.8675 - Accuracy: 0.6618 - F1: 0.6167
sub_4:Test (Best Model) - Loss: 0.5994 - Accuracy: 0.8841 - F1: 0.8827
sub_3:Test (Best Model) - Loss: 1.1432 - Accuracy: 0.6522 - F1: 0.6107
sub_9:Test (Best Model) - Loss: 0.8609 - Accuracy: 0.6765 - F1: 0.6168
sub_25:Test (Best Model) - Loss: 0.7926 - Accuracy: 0.7794 - F1: 0.7551
sub_29:Test (Best Model) - Loss: 0.4750 - Accuracy: 0.9265 - F1: 0.9292
sub_28:Test (Best Model) - Loss: 1.5383 - Accuracy: 0.4412 - F1: 0.3508
sub_14:Test (Best Model) - Loss: 0.9230 - Accuracy: 0.5588 - F1: 0.6024
sub_16:Test (Best Model) - Loss: 0.9057 - Accuracy: 0.6471 - F1: 0.6018
sub_5:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.7647 - F1: 0.7133
sub_22:Test (Best Model) - Loss: 1.1885 - Accuracy: 0.5652 - F1: 0.5118
sub_24:Test (Best Model) - Loss: 1.0175 - Accuracy: 0.7059 - F1: 0.6306
sub_21:Test (Best Model) - Loss: 0.4658 - Accuracy: 0.9265 - F1: 0.9277
sub_10:Test (Best Model) - Loss: 1.0231 - Accuracy: 0.4853 - F1: 0.4726
sub_8:Test (Best Model) - Loss: 0.8894 - Accuracy: 0.7059 - F1: 0.6452
sub_18:Test (Best Model) - Loss: 1.1134 - Accuracy: 0.6029 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.9705 - Accuracy: 0.7206 - F1: 0.6474
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.7681 - F1: 0.7645
sub_2:Test (Best Model) - Loss: 0.9021 - Accuracy: 0.7059 - F1: 0.6435
sub_17:Test (Best Model) - Loss: 1.1009 - Accuracy: 0.5797 - F1: 0.5285
sub_27:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.5652 - F1: 0.5076
sub_11:Test (Best Model) - Loss: 0.9181 - Accuracy: 0.7391 - F1: 0.6882
sub_23:Test (Best Model) - Loss: 1.1041 - Accuracy: 0.7059 - F1: 0.6231
sub_26:Test (Best Model) - Loss: 1.2344 - Accuracy: 0.4559 - F1: 0.4294
sub_13:Test (Best Model) - Loss: 1.0867 - Accuracy: 0.5362 - F1: 0.5002
sub_9:Test (Best Model) - Loss: 0.8764 - Accuracy: 0.6176 - F1: 0.5623
sub_25:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.7647 - F1: 0.7321
sub_15:Test (Best Model) - Loss: 0.6018 - Accuracy: 0.8235 - F1: 0.8284
sub_3:Test (Best Model) - Loss: 1.0193 - Accuracy: 0.6812 - F1: 0.6426
sub_20:Test (Best Model) - Loss: 0.9614 - Accuracy: 0.6912 - F1: 0.6488
sub_19:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.7206 - F1: 0.7105
sub_6:Test (Best Model) - Loss: 1.5409 - Accuracy: 0.4783 - F1: 0.3756
sub_4:Test (Best Model) - Loss: 0.5591 - Accuracy: 0.8551 - F1: 0.8516
sub_10:Test (Best Model) - Loss: 0.9987 - Accuracy: 0.4853 - F1: 0.4889
sub_28:Test (Best Model) - Loss: 1.3942 - Accuracy: 0.4559 - F1: 0.3920
sub_22:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.5507 - F1: 0.5056
sub_21:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.8382 - F1: 0.8295
sub_16:Test (Best Model) - Loss: 0.8785 - Accuracy: 0.6176 - F1: 0.5532
sub_18:Test (Best Model) - Loss: 0.9702 - Accuracy: 0.5882 - F1: 0.6095
sub_14:Test (Best Model) - Loss: 1.0389 - Accuracy: 0.5147 - F1: 0.5633
sub_11:Test (Best Model) - Loss: 0.8862 - Accuracy: 0.7391 - F1: 0.6882
sub_5:Test (Best Model) - Loss: 1.0150 - Accuracy: 0.7059 - F1: 0.6232
sub_24:Test (Best Model) - Loss: 0.9189 - Accuracy: 0.7206 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.8800 - Accuracy: 0.7206 - F1: 0.6495
sub_7:Test (Best Model) - Loss: 0.9741 - Accuracy: 0.7206 - F1: 0.6507
sub_29:Test (Best Model) - Loss: 0.4090 - Accuracy: 0.9118 - F1: 0.9168
sub_13:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.5362 - F1: 0.5069
sub_12:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.7681 - F1: 0.7741
sub_25:Test (Best Model) - Loss: 0.7618 - Accuracy: 0.7794 - F1: 0.7837
sub_26:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.4118 - F1: 0.3758
sub_2:Test (Best Model) - Loss: 0.9214 - Accuracy: 0.7059 - F1: 0.6435
sub_1:Test (Best Model) - Loss: 0.7214 - Accuracy: 0.7246 - F1: 0.7157
sub_17:Test (Best Model) - Loss: 1.0787 - Accuracy: 0.5507 - F1: 0.4958
sub_27:Test (Best Model) - Loss: 1.1009 - Accuracy: 0.5797 - F1: 0.5285
sub_10:Test (Best Model) - Loss: 0.8906 - Accuracy: 0.6957 - F1: 0.6414
sub_23:Test (Best Model) - Loss: 0.9987 - Accuracy: 0.7059 - F1: 0.6199
sub_9:Test (Best Model) - Loss: 0.9446 - Accuracy: 0.5588 - F1: 0.4989
sub_22:Test (Best Model) - Loss: 1.1522 - Accuracy: 0.4783 - F1: 0.4304
sub_6:Test (Best Model) - Loss: 0.9604 - Accuracy: 0.5362 - F1: 0.4632
sub_11:Test (Best Model) - Loss: 0.7980 - Accuracy: 0.7391 - F1: 0.7444
sub_19:Test (Best Model) - Loss: 0.8299 - Accuracy: 0.6765 - F1: 0.6868
sub_20:Test (Best Model) - Loss: 0.9521 - Accuracy: 0.6912 - F1: 0.6428
sub_4:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.8841 - F1: 0.8839
sub_15:Test (Best Model) - Loss: 0.5595 - Accuracy: 0.8235 - F1: 0.8231
sub_8:Test (Best Model) - Loss: 0.9164 - Accuracy: 0.5588 - F1: 0.5916
sub_25:Test (Best Model) - Loss: 0.8332 - Accuracy: 0.6618 - F1: 0.6330
sub_28:Test (Best Model) - Loss: 1.4791 - Accuracy: 0.4412 - F1: 0.3690
sub_18:Test (Best Model) - Loss: 0.9665 - Accuracy: 0.5441 - F1: 0.5490
sub_16:Test (Best Model) - Loss: 0.8445 - Accuracy: 0.6912 - F1: 0.6480
sub_5:Test (Best Model) - Loss: 0.8843 - Accuracy: 0.7353 - F1: 0.6631
sub_3:Test (Best Model) - Loss: 1.0389 - Accuracy: 0.6812 - F1: 0.6426
sub_14:Test (Best Model) - Loss: 1.1080 - Accuracy: 0.5294 - F1: 0.5435
sub_24:Test (Best Model) - Loss: 0.8711 - Accuracy: 0.7353 - F1: 0.6500
sub_2:Test (Best Model) - Loss: 0.9435 - Accuracy: 0.6765 - F1: 0.6111
sub_21:Test (Best Model) - Loss: 0.4811 - Accuracy: 0.8971 - F1: 0.8968
sub_22:Test (Best Model) - Loss: 0.9710 - Accuracy: 0.6912 - F1: 0.6642
sub_12:Test (Best Model) - Loss: 0.7220 - Accuracy: 0.7681 - F1: 0.7682
sub_26:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.4706 - F1: 0.4549
sub_29:Test (Best Model) - Loss: 0.4014 - Accuracy: 0.8824 - F1: 0.8831
sub_13:Test (Best Model) - Loss: 1.1709 - Accuracy: 0.5652 - F1: 0.5341
sub_23:Test (Best Model) - Loss: 1.1171 - Accuracy: 0.6471 - F1: 0.5803
sub_17:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.7206 - F1: 0.6717
sub_27:Test (Best Model) - Loss: 1.0787 - Accuracy: 0.5507 - F1: 0.4958
sub_18:Test (Best Model) - Loss: 0.9204 - Accuracy: 0.6029 - F1: 0.6026
sub_8:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.6471 - F1: 0.6770
sub_10:Test (Best Model) - Loss: 0.9091 - Accuracy: 0.6667 - F1: 0.6087
sub_20:Test (Best Model) - Loss: 0.9568 - Accuracy: 0.6324 - F1: 0.5675
sub_2:Test (Best Model) - Loss: 0.8407 - Accuracy: 0.7059 - F1: 0.6435
sub_15:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.8382 - F1: 0.8428
sub_1:Test (Best Model) - Loss: 0.7308 - Accuracy: 0.7246 - F1: 0.7169
sub_25:Test (Best Model) - Loss: 0.9024 - Accuracy: 0.6765 - F1: 0.6250
sub_19:Test (Best Model) - Loss: 0.8952 - Accuracy: 0.6471 - F1: 0.6491
sub_4:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.7391 - F1: 0.6877
sub_7:Test (Best Model) - Loss: 0.9725 - Accuracy: 0.7206 - F1: 0.6446
sub_3:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.7681 - F1: 0.7711
sub_9:Test (Best Model) - Loss: 0.8181 - Accuracy: 0.6765 - F1: 0.6307
sub_28:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.4853 - F1: 0.4256
sub_22:Test (Best Model) - Loss: 1.0647 - Accuracy: 0.6029 - F1: 0.5616
sub_14:Test (Best Model) - Loss: 0.9110 - Accuracy: 0.5147 - F1: 0.4841
sub_5:Test (Best Model) - Loss: 0.9274 - Accuracy: 0.7353 - F1: 0.6599
sub_21:Test (Best Model) - Loss: 0.7344 - Accuracy: 0.8088 - F1: 0.7893
sub_16:Test (Best Model) - Loss: 0.6620 - Accuracy: 0.7353 - F1: 0.7159
sub_13:Test (Best Model) - Loss: 1.4077 - Accuracy: 0.4559 - F1: 0.3313
sub_6:Test (Best Model) - Loss: 0.8932 - Accuracy: 0.6812 - F1: 0.6785
sub_24:Test (Best Model) - Loss: 0.9282 - Accuracy: 0.7206 - F1: 0.6375
sub_8:Test (Best Model) - Loss: 0.9480 - Accuracy: 0.6176 - F1: 0.5884
sub_29:Test (Best Model) - Loss: 0.7939 - Accuracy: 0.7246 - F1: 0.6536
sub_11:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.7391 - F1: 0.7192
sub_23:Test (Best Model) - Loss: 1.1526 - Accuracy: 0.5652 - F1: 0.5180
sub_18:Test (Best Model) - Loss: 0.9971 - Accuracy: 0.5882 - F1: 0.5633
sub_20:Test (Best Model) - Loss: 0.8344 - Accuracy: 0.6812 - F1: 0.6671
sub_7:Test (Best Model) - Loss: 0.7361 - Accuracy: 0.8529 - F1: 0.8486
sub_12:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.7794 - F1: 0.7917
sub_26:Test (Best Model) - Loss: 1.6752 - Accuracy: 0.3529 - F1: 0.3632
sub_27:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.7206 - F1: 0.6717
sub_17:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.7059 - F1: 0.6952
sub_10:Test (Best Model) - Loss: 0.8973 - Accuracy: 0.6522 - F1: 0.5703
sub_3:Test (Best Model) - Loss: 0.7729 - Accuracy: 0.7971 - F1: 0.8105
sub_1:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.7536 - F1: 0.7567
sub_25:Test (Best Model) - Loss: 0.7894 - Accuracy: 0.6765 - F1: 0.6324
sub_15:Test (Best Model) - Loss: 0.9361 - Accuracy: 0.6912 - F1: 0.6420
sub_4:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.7536 - F1: 0.7395
sub_5:Test (Best Model) - Loss: 0.8832 - Accuracy: 0.7206 - F1: 0.6450
sub_6:Test (Best Model) - Loss: 0.8670 - Accuracy: 0.6667 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.7670 - Accuracy: 0.7500 - F1: 0.7457
sub_21:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.7941 - F1: 0.7632
sub_8:Test (Best Model) - Loss: 0.9101 - Accuracy: 0.6029 - F1: 0.5974
sub_9:Test (Best Model) - Loss: 0.9370 - Accuracy: 0.6471 - F1: 0.6313
sub_14:Test (Best Model) - Loss: 0.8422 - Accuracy: 0.6471 - F1: 0.6366
sub_2:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.4638 - F1: 0.3505
sub_19:Test (Best Model) - Loss: 1.2040 - Accuracy: 0.5294 - F1: 0.4823
sub_13:Test (Best Model) - Loss: 1.2098 - Accuracy: 0.5147 - F1: 0.4489
sub_28:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.4559 - F1: 0.3084
sub_23:Test (Best Model) - Loss: 1.1116 - Accuracy: 0.5362 - F1: 0.4908
sub_20:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.7391 - F1: 0.7380
sub_11:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.8551 - F1: 0.8605
sub_18:Test (Best Model) - Loss: 0.9673 - Accuracy: 0.5735 - F1: 0.5606
sub_3:Test (Best Model) - Loss: 0.7749 - Accuracy: 0.7971 - F1: 0.8036
sub_29:Test (Best Model) - Loss: 0.8599 - Accuracy: 0.7101 - F1: 0.6407
sub_22:Test (Best Model) - Loss: 0.9908 - Accuracy: 0.5882 - F1: 0.5755
sub_7:Test (Best Model) - Loss: 0.7961 - Accuracy: 0.7059 - F1: 0.6829
sub_12:Test (Best Model) - Loss: 0.7645 - Accuracy: 0.7353 - F1: 0.7463
sub_4:Test (Best Model) - Loss: 0.8416 - Accuracy: 0.6812 - F1: 0.6399
sub_24:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.6912 - F1: 0.7092
sub_26:Test (Best Model) - Loss: 1.0065 - Accuracy: 0.5882 - F1: 0.5538
sub_10:Test (Best Model) - Loss: 0.9461 - Accuracy: 0.5942 - F1: 0.5270
sub_17:Test (Best Model) - Loss: 0.9132 - Accuracy: 0.6324 - F1: 0.5947
sub_16:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.8088 - F1: 0.8020
sub_27:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.7059 - F1: 0.6952
sub_15:Test (Best Model) - Loss: 1.0868 - Accuracy: 0.5588 - F1: 0.4826
sub_5:Test (Best Model) - Loss: 0.9097 - Accuracy: 0.7353 - F1: 0.6631
sub_11:Test (Best Model) - Loss: 0.7596 - Accuracy: 0.7681 - F1: 0.7680
sub_25:Test (Best Model) - Loss: 0.7542 - Accuracy: 0.7059 - F1: 0.6809
sub_9:Test (Best Model) - Loss: 0.9698 - Accuracy: 0.6765 - F1: 0.6616
sub_1:Test (Best Model) - Loss: 0.9420 - Accuracy: 0.7353 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.7206 - F1: 0.7228
sub_8:Test (Best Model) - Loss: 1.0421 - Accuracy: 0.4853 - F1: 0.5053
sub_23:Test (Best Model) - Loss: 1.1234 - Accuracy: 0.5942 - F1: 0.5448
sub_6:Test (Best Model) - Loss: 0.8361 - Accuracy: 0.6812 - F1: 0.6060
sub_13:Test (Best Model) - Loss: 1.2701 - Accuracy: 0.4559 - F1: 0.3355
sub_19:Test (Best Model) - Loss: 1.2058 - Accuracy: 0.5000 - F1: 0.4538
sub_2:Test (Best Model) - Loss: 1.1597 - Accuracy: 0.5217 - F1: 0.4432
sub_12:Test (Best Model) - Loss: 0.7925 - Accuracy: 0.8235 - F1: 0.8317
sub_18:Test (Best Model) - Loss: 1.1650 - Accuracy: 0.5147 - F1: 0.4924
sub_7:Test (Best Model) - Loss: 0.7925 - Accuracy: 0.7353 - F1: 0.7175
sub_28:Test (Best Model) - Loss: 1.2802 - Accuracy: 0.5147 - F1: 0.4049
sub_21:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.8529 - F1: 0.8495
sub_22:Test (Best Model) - Loss: 0.9796 - Accuracy: 0.6029 - F1: 0.5704
sub_29:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.7246 - F1: 0.6536
sub_3:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.7536 - F1: 0.7630
sub_20:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.7536 - F1: 0.7556
sub_16:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.8382 - F1: 0.8305
sub_24:Test (Best Model) - Loss: 0.8235 - Accuracy: 0.6471 - F1: 0.6620
sub_10:Test (Best Model) - Loss: 1.0377 - Accuracy: 0.6377 - F1: 0.5656
sub_4:Test (Best Model) - Loss: 0.7854 - Accuracy: 0.7536 - F1: 0.6961
sub_27:Test (Best Model) - Loss: 0.9132 - Accuracy: 0.6324 - F1: 0.5947
sub_11:Test (Best Model) - Loss: 0.7523 - Accuracy: 0.7391 - F1: 0.7370
sub_17:Test (Best Model) - Loss: 0.8252 - Accuracy: 0.6765 - F1: 0.6194
sub_1:Test (Best Model) - Loss: 0.8431 - Accuracy: 0.7059 - F1: 0.6484
sub_15:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.5147 - F1: 0.4029
sub_6:Test (Best Model) - Loss: 0.7854 - Accuracy: 0.6957 - F1: 0.6212
sub_26:Test (Best Model) - Loss: 1.2231 - Accuracy: 0.5294 - F1: 0.5008
sub_9:Test (Best Model) - Loss: 1.0224 - Accuracy: 0.6471 - F1: 0.6327
sub_14:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.6765 - F1: 0.6787
sub_13:Test (Best Model) - Loss: 1.4101 - Accuracy: 0.4706 - F1: 0.3683
sub_19:Test (Best Model) - Loss: 1.1264 - Accuracy: 0.5294 - F1: 0.4861
sub_2:Test (Best Model) - Loss: 1.0216 - Accuracy: 0.5797 - F1: 0.5211
sub_23:Test (Best Model) - Loss: 1.1920 - Accuracy: 0.5507 - F1: 0.5008
sub_16:Test (Best Model) - Loss: 0.7959 - Accuracy: 0.8382 - F1: 0.8339
sub_12:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.7941 - F1: 0.7996
sub_3:Test (Best Model) - Loss: 0.8608 - Accuracy: 0.6377 - F1: 0.6178
sub_28:Test (Best Model) - Loss: 1.2784 - Accuracy: 0.4706 - F1: 0.3377
sub_20:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.7246 - F1: 0.7193
sub_24:Test (Best Model) - Loss: 0.7592 - Accuracy: 0.7500 - F1: 0.7610
sub_4:Test (Best Model) - Loss: 0.8163 - Accuracy: 0.7246 - F1: 0.6789
sub_6:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.6812 - F1: 0.6100
sub_7:Test (Best Model) - Loss: 0.9676 - Accuracy: 0.5735 - F1: 0.4972
sub_29:Test (Best Model) - Loss: 0.8950 - Accuracy: 0.7101 - F1: 0.6407
sub_22:Test (Best Model) - Loss: 1.0493 - Accuracy: 0.5294 - F1: 0.5357
sub_21:Test (Best Model) - Loss: 0.4843 - Accuracy: 0.8676 - F1: 0.8588
sub_14:Test (Best Model) - Loss: 0.9418 - Accuracy: 0.6324 - F1: 0.5920
sub_26:Test (Best Model) - Loss: 1.2382 - Accuracy: 0.5588 - F1: 0.5186
sub_2:Test (Best Model) - Loss: 1.1579 - Accuracy: 0.5507 - F1: 0.4707
sub_15:Test (Best Model) - Loss: 1.0889 - Accuracy: 0.5294 - F1: 0.4283
sub_17:Test (Best Model) - Loss: 0.8793 - Accuracy: 0.6618 - F1: 0.6313
sub_9:Test (Best Model) - Loss: 1.1988 - Accuracy: 0.5294 - F1: 0.4794
sub_27:Test (Best Model) - Loss: 0.8252 - Accuracy: 0.6765 - F1: 0.6194
sub_23:Test (Best Model) - Loss: 1.2407 - Accuracy: 0.5217 - F1: 0.4770
sub_1:Test (Best Model) - Loss: 0.9937 - Accuracy: 0.6618 - F1: 0.6398
sub_24:Test (Best Model) - Loss: 0.7714 - Accuracy: 0.7500 - F1: 0.7396
sub_28:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.4853 - F1: 0.3483
sub_19:Test (Best Model) - Loss: 1.1980 - Accuracy: 0.4706 - F1: 0.4295
sub_12:Test (Best Model) - Loss: 0.7663 - Accuracy: 0.7059 - F1: 0.6775
sub_13:Test (Best Model) - Loss: 1.2857 - Accuracy: 0.5441 - F1: 0.4935
sub_6:Test (Best Model) - Loss: 0.8150 - Accuracy: 0.7246 - F1: 0.6651
sub_29:Test (Best Model) - Loss: 0.7902 - Accuracy: 0.6812 - F1: 0.6268
sub_7:Test (Best Model) - Loss: 0.7190 - Accuracy: 0.7353 - F1: 0.6987
sub_21:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.8529 - F1: 0.8553
sub_9:Test (Best Model) - Loss: 1.0397 - Accuracy: 0.5588 - F1: 0.5460
sub_20:Test (Best Model) - Loss: 0.7336 - Accuracy: 0.7536 - F1: 0.7477
sub_2:Test (Best Model) - Loss: 1.1477 - Accuracy: 0.5942 - F1: 0.5355
sub_15:Test (Best Model) - Loss: 1.0550 - Accuracy: 0.7059 - F1: 0.6389
sub_1:Test (Best Model) - Loss: 0.8655 - Accuracy: 0.7059 - F1: 0.6775
sub_27:Test (Best Model) - Loss: 0.8793 - Accuracy: 0.6618 - F1: 0.6313
sub_28:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4559 - F1: 0.3081
sub_24:Test (Best Model) - Loss: 0.7903 - Accuracy: 0.6912 - F1: 0.7166
sub_19:Test (Best Model) - Loss: 1.1327 - Accuracy: 0.6471 - F1: 0.5862
sub_26:Test (Best Model) - Loss: 1.0641 - Accuracy: 0.6471 - F1: 0.6522
sub_1:Test (Best Model) - Loss: 0.9470 - Accuracy: 0.6912 - F1: 0.6348
sub_26:Test (Best Model) - Loss: 0.7585 - Accuracy: 0.6765 - F1: 0.6760

=== Summary Results ===

acc: 65.97 ± 9.18
F1: 62.84 ± 10.10
acc-in: 96.32 ± 2.21
F1-in: 96.09 ± 2.57
