lr: 0.001
sub_1:Test (Best Model) - Loss: 2.1975 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 3.3061 - Accuracy: 0.6250 - F1: 0.6190
sub_1:Test (Best Model) - Loss: 2.8442 - Accuracy: 0.5000 - F1: 0.4980
sub_1:Test (Best Model) - Loss: 1.9532 - Accuracy: 0.5938 - F1: 0.5589
sub_1:Test (Best Model) - Loss: 2.5147 - Accuracy: 0.5625 - F1: 0.5466
sub_1:Test (Best Model) - Loss: 1.5054 - Accuracy: 0.6970 - F1: 0.6726
sub_1:Test (Best Model) - Loss: 3.4879 - Accuracy: 0.6061 - F1: 0.5662
sub_1:Test (Best Model) - Loss: 2.4953 - Accuracy: 0.6667 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 4.4420 - Accuracy: 0.5152 - F1: 0.4762
sub_1:Test (Best Model) - Loss: 3.1458 - Accuracy: 0.6364 - F1: 0.6192
sub_1:Test (Best Model) - Loss: 2.6517 - Accuracy: 0.5938 - F1: 0.5836
sub_1:Test (Best Model) - Loss: 2.7628 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 2.0648 - Accuracy: 0.5625 - F1: 0.5608
sub_1:Test (Best Model) - Loss: 1.3376 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 2.4505 - Accuracy: 0.6250 - F1: 0.6113
sub_2:Test (Best Model) - Loss: 3.5915 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 2.5304 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 2.5300 - Accuracy: 0.6667 - F1: 0.6459
sub_2:Test (Best Model) - Loss: 5.0706 - Accuracy: 0.6364 - F1: 0.5909
sub_2:Test (Best Model) - Loss: 3.7452 - Accuracy: 0.6061 - F1: 0.5662
sub_2:Test (Best Model) - Loss: 5.6415 - Accuracy: 0.5000 - F1: 0.4921
sub_2:Test (Best Model) - Loss: 2.4637 - Accuracy: 0.5000 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 1.7611 - Accuracy: 0.5625 - F1: 0.5466
sub_2:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.5312 - F1: 0.5077
sub_2:Test (Best Model) - Loss: 1.9566 - Accuracy: 0.5625 - F1: 0.5556
sub_2:Test (Best Model) - Loss: 3.2026 - Accuracy: 0.4545 - F1: 0.3543
sub_2:Test (Best Model) - Loss: 3.5362 - Accuracy: 0.5152 - F1: 0.5147
sub_2:Test (Best Model) - Loss: 1.9959 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 2.6982 - Accuracy: 0.7576 - F1: 0.7574
sub_2:Test (Best Model) - Loss: 2.4759 - Accuracy: 0.6061 - F1: 0.6046
sub_3:Test (Best Model) - Loss: 3.5903 - Accuracy: 0.4375 - F1: 0.4353
sub_3:Test (Best Model) - Loss: 3.7969 - Accuracy: 0.5312 - F1: 0.5308
sub_3:Test (Best Model) - Loss: 3.5618 - Accuracy: 0.5312 - F1: 0.5308
sub_3:Test (Best Model) - Loss: 3.5612 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 3.2611 - Accuracy: 0.3438 - F1: 0.3431
sub_3:Test (Best Model) - Loss: 3.4013 - Accuracy: 0.3939 - F1: 0.3889
sub_3:Test (Best Model) - Loss: 3.8331 - Accuracy: 0.3030 - F1: 0.2926
sub_3:Test (Best Model) - Loss: 2.9497 - Accuracy: 0.4848 - F1: 0.4848
sub_3:Test (Best Model) - Loss: 2.5136 - Accuracy: 0.4848 - F1: 0.4527
sub_3:Test (Best Model) - Loss: 4.8639 - Accuracy: 0.3636 - F1: 0.3636
sub_3:Test (Best Model) - Loss: 4.9352 - Accuracy: 0.4242 - F1: 0.4157
sub_3:Test (Best Model) - Loss: 3.5255 - Accuracy: 0.4545 - F1: 0.3864
sub_3:Test (Best Model) - Loss: 3.1521 - Accuracy: 0.4242 - F1: 0.4046
sub_3:Test (Best Model) - Loss: 3.8171 - Accuracy: 0.3939 - F1: 0.3452
sub_3:Test (Best Model) - Loss: 4.5125 - Accuracy: 0.4545 - F1: 0.4417
sub_4:Test (Best Model) - Loss: 4.5381 - Accuracy: 0.3636 - F1: 0.3541
sub_4:Test (Best Model) - Loss: 2.1670 - Accuracy: 0.5455 - F1: 0.5299
sub_4:Test (Best Model) - Loss: 2.6349 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 2.7053 - Accuracy: 0.5152 - F1: 0.5111
sub_4:Test (Best Model) - Loss: 3.2930 - Accuracy: 0.5152 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 3.2945 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 4.2029 - Accuracy: 0.4848 - F1: 0.4672
sub_4:Test (Best Model) - Loss: 2.3862 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 5.5172 - Accuracy: 0.4242 - F1: 0.4221
sub_4:Test (Best Model) - Loss: 4.3094 - Accuracy: 0.5455 - F1: 0.4457
sub_4:Test (Best Model) - Loss: 3.0098 - Accuracy: 0.4242 - F1: 0.4046
sub_4:Test (Best Model) - Loss: 2.1191 - Accuracy: 0.5152 - F1: 0.5111
sub_4:Test (Best Model) - Loss: 1.8443 - Accuracy: 0.5455 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 0.9214 - Accuracy: 0.6970 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 1.6924 - Accuracy: 0.6970 - F1: 0.6967
sub_5:Test (Best Model) - Loss: 5.6591 - Accuracy: 0.4062 - F1: 0.4057
sub_5:Test (Best Model) - Loss: 4.2022 - Accuracy: 0.4375 - F1: 0.4353
sub_5:Test (Best Model) - Loss: 7.7461 - Accuracy: 0.4688 - F1: 0.4682
sub_5:Test (Best Model) - Loss: 5.8757 - Accuracy: 0.4688 - F1: 0.4682
sub_5:Test (Best Model) - Loss: 4.5286 - Accuracy: 0.3750 - F1: 0.3725
sub_5:Test (Best Model) - Loss: 1.9797 - Accuracy: 0.6562 - F1: 0.6476
sub_5:Test (Best Model) - Loss: 2.0931 - Accuracy: 0.4375 - F1: 0.4353
sub_5:Test (Best Model) - Loss: 1.5513 - Accuracy: 0.4375 - F1: 0.4353
sub_5:Test (Best Model) - Loss: 1.2610 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 1.6244 - Accuracy: 0.6562 - F1: 0.5883
sub_5:Test (Best Model) - Loss: 2.6095 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 2.9523 - Accuracy: 0.4062 - F1: 0.4057
sub_5:Test (Best Model) - Loss: 3.6702 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 3.9611 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 2.2789 - Accuracy: 0.5625 - F1: 0.5333
sub_6:Test (Best Model) - Loss: 3.6331 - Accuracy: 0.6250 - F1: 0.6000
sub_6:Test (Best Model) - Loss: 4.2578 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 3.3592 - Accuracy: 0.4688 - F1: 0.4421
sub_6:Test (Best Model) - Loss: 2.6485 - Accuracy: 0.4688 - F1: 0.4640
sub_6:Test (Best Model) - Loss: 3.0467 - Accuracy: 0.5312 - F1: 0.5308
sub_6:Test (Best Model) - Loss: 5.8041 - Accuracy: 0.4545 - F1: 0.4288
sub_6:Test (Best Model) - Loss: 4.9226 - Accuracy: 0.4545 - F1: 0.3543
sub_6:Test (Best Model) - Loss: 3.8419 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 4.8541 - Accuracy: 0.4848 - F1: 0.4328
sub_6:Test (Best Model) - Loss: 8.1925 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 4.2100 - Accuracy: 0.3636 - F1: 0.3541
sub_6:Test (Best Model) - Loss: 3.0737 - Accuracy: 0.4848 - F1: 0.4527
sub_6:Test (Best Model) - Loss: 3.9481 - Accuracy: 0.5758 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 2.7632 - Accuracy: 0.6061 - F1: 0.5815
sub_6:Test (Best Model) - Loss: 2.2777 - Accuracy: 0.6667 - F1: 0.6330
sub_7:Test (Best Model) - Loss: 1.8521 - Accuracy: 0.5938 - F1: 0.5589
sub_7:Test (Best Model) - Loss: 2.9379 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 2.8905 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 3.0210 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 4.1324 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 5.5971 - Accuracy: 0.4375 - F1: 0.4375
sub_7:Test (Best Model) - Loss: 3.8229 - Accuracy: 0.3750 - F1: 0.3750
sub_7:Test (Best Model) - Loss: 3.9396 - Accuracy: 0.3438 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 4.8457 - Accuracy: 0.2812 - F1: 0.2805
sub_7:Test (Best Model) - Loss: 2.8501 - Accuracy: 0.3750 - F1: 0.3725
sub_7:Test (Best Model) - Loss: 3.3305 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 4.0614 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 5.0674 - Accuracy: 0.4688 - F1: 0.4555
sub_7:Test (Best Model) - Loss: 2.9905 - Accuracy: 0.5625 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 2.4152 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 4.5928 - Accuracy: 0.5000 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 4.7989 - Accuracy: 0.4375 - F1: 0.4170
sub_8:Test (Best Model) - Loss: 4.0843 - Accuracy: 0.4375 - F1: 0.4353
sub_8:Test (Best Model) - Loss: 2.8017 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 4.8291 - Accuracy: 0.5000 - F1: 0.4818
sub_8:Test (Best Model) - Loss: 1.7717 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 2.6721 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 4.7870 - Accuracy: 0.5000 - F1: 0.4980
sub_8:Test (Best Model) - Loss: 6.9172 - Accuracy: 0.5312 - F1: 0.5271
sub_8:Test (Best Model) - Loss: 4.1227 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 6.7827 - Accuracy: 0.3125 - F1: 0.3098
sub_8:Test (Best Model) - Loss: 3.5722 - Accuracy: 0.3750 - F1: 0.3750
sub_8:Test (Best Model) - Loss: 3.4207 - Accuracy: 0.4062 - F1: 0.4057
sub_8:Test (Best Model) - Loss: 3.3284 - Accuracy: 0.3438 - F1: 0.3379
sub_8:Test (Best Model) - Loss: 2.5091 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 1.9600 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 2.7885 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 1.2099 - Accuracy: 0.6875 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 2.6716 - Accuracy: 0.6562 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 2.6319 - Accuracy: 0.7188 - F1: 0.6632
sub_9:Test (Best Model) - Loss: 2.6053 - Accuracy: 0.5625 - F1: 0.5556
sub_9:Test (Best Model) - Loss: 3.4722 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 2.7046 - Accuracy: 0.5000 - F1: 0.5000
sub_9:Test (Best Model) - Loss: 3.8453 - Accuracy: 0.6250 - F1: 0.5844
sub_9:Test (Best Model) - Loss: 8.4097 - Accuracy: 0.3750 - F1: 0.3651
sub_9:Test (Best Model) - Loss: 4.0176 - Accuracy: 0.6875 - F1: 0.6875
sub_9:Test (Best Model) - Loss: 6.4973 - Accuracy: 0.5000 - F1: 0.4980
sub_9:Test (Best Model) - Loss: 3.5028 - Accuracy: 0.5000 - F1: 0.4980
sub_9:Test (Best Model) - Loss: 2.7405 - Accuracy: 0.7188 - F1: 0.7185
sub_10:Test (Best Model) - Loss: 3.1652 - Accuracy: 0.3750 - F1: 0.3651
sub_10:Test (Best Model) - Loss: 2.4797 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 1.7806 - Accuracy: 0.4375 - F1: 0.4170
sub_10:Test (Best Model) - Loss: 3.9180 - Accuracy: 0.4688 - F1: 0.4421
sub_10:Test (Best Model) - Loss: 3.8869 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 4.0907 - Accuracy: 0.4375 - F1: 0.4375
sub_10:Test (Best Model) - Loss: 3.4709 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 3.6008 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 2.6718 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 5.2324 - Accuracy: 0.3125 - F1: 0.3098
sub_10:Test (Best Model) - Loss: 4.3910 - Accuracy: 0.4848 - F1: 0.4527
sub_10:Test (Best Model) - Loss: 3.8483 - Accuracy: 0.3939 - F1: 0.3934
sub_10:Test (Best Model) - Loss: 2.4195 - Accuracy: 0.5758 - F1: 0.5558
sub_10:Test (Best Model) - Loss: 3.3636 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 4.0264 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 3.7390 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 4.4448 - Accuracy: 0.4242 - F1: 0.4046
sub_11:Test (Best Model) - Loss: 6.3929 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 2.2507 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 3.3318 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 2.1476 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 3.1255 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 2.3637 - Accuracy: 0.5758 - F1: 0.5558
sub_11:Test (Best Model) - Loss: 3.1535 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 3.7762 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 2.9349 - Accuracy: 0.4848 - F1: 0.3718
sub_11:Test (Best Model) - Loss: 1.7723 - Accuracy: 0.4848 - F1: 0.4772
sub_11:Test (Best Model) - Loss: 3.8012 - Accuracy: 0.5758 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 3.3605 - Accuracy: 0.5758 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 2.7498 - Accuracy: 0.5455 - F1: 0.5171
sub_12:Test (Best Model) - Loss: 2.7467 - Accuracy: 0.5625 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 2.7004 - Accuracy: 0.5000 - F1: 0.4667
sub_12:Test (Best Model) - Loss: 4.5847 - Accuracy: 0.4688 - F1: 0.4640
sub_12:Test (Best Model) - Loss: 5.1792 - Accuracy: 0.4062 - F1: 0.3914
sub_12:Test (Best Model) - Loss: 4.5847 - Accuracy: 0.4688 - F1: 0.4231
sub_12:Test (Best Model) - Loss: 3.2762 - Accuracy: 0.4242 - F1: 0.4157
sub_12:Test (Best Model) - Loss: 2.9738 - Accuracy: 0.5758 - F1: 0.5417
sub_12:Test (Best Model) - Loss: 2.8806 - Accuracy: 0.5152 - F1: 0.4261
sub_12:Test (Best Model) - Loss: 4.5483 - Accuracy: 0.5455 - F1: 0.4995
sub_12:Test (Best Model) - Loss: 2.6795 - Accuracy: 0.6364 - F1: 0.6278
sub_12:Test (Best Model) - Loss: 4.8497 - Accuracy: 0.5938 - F1: 0.5393
sub_12:Test (Best Model) - Loss: 4.6629 - Accuracy: 0.4688 - F1: 0.4421
sub_12:Test (Best Model) - Loss: 4.2489 - Accuracy: 0.3750 - F1: 0.3725
sub_12:Test (Best Model) - Loss: 4.4978 - Accuracy: 0.5938 - F1: 0.5733
sub_12:Test (Best Model) - Loss: 3.2233 - Accuracy: 0.5938 - F1: 0.5393
sub_13:Test (Best Model) - Loss: 1.0556 - Accuracy: 0.6875 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 2.3148 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 1.6481 - Accuracy: 0.6250 - F1: 0.6190
sub_13:Test (Best Model) - Loss: 2.5370 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 1.7930 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 3.5583 - Accuracy: 0.4545 - F1: 0.4417
sub_13:Test (Best Model) - Loss: 4.8475 - Accuracy: 0.4242 - F1: 0.4221
sub_13:Test (Best Model) - Loss: 2.5799 - Accuracy: 0.6061 - F1: 0.6046
sub_13:Test (Best Model) - Loss: 2.9679 - Accuracy: 0.3333 - F1: 0.3278
sub_13:Test (Best Model) - Loss: 3.5275 - Accuracy: 0.3636 - F1: 0.2993
sub_13:Test (Best Model) - Loss: 1.9725 - Accuracy: 0.5000 - F1: 0.4818
sub_13:Test (Best Model) - Loss: 1.7625 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 0.7466 - Accuracy: 0.6562 - F1: 0.6476
sub_13:Test (Best Model) - Loss: 1.6756 - Accuracy: 0.6250 - F1: 0.6113
sub_13:Test (Best Model) - Loss: 1.9940 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 2.6212 - Accuracy: 0.4688 - F1: 0.4231
sub_14:Test (Best Model) - Loss: 2.3181 - Accuracy: 0.5938 - F1: 0.5393
sub_14:Test (Best Model) - Loss: 3.2919 - Accuracy: 0.4062 - F1: 0.4010
sub_14:Test (Best Model) - Loss: 2.5154 - Accuracy: 0.5000 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 2.6065 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 3.7643 - Accuracy: 0.3750 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 1.9109 - Accuracy: 0.4688 - F1: 0.4640
sub_14:Test (Best Model) - Loss: 3.0375 - Accuracy: 0.4688 - F1: 0.4682
sub_14:Test (Best Model) - Loss: 2.3833 - Accuracy: 0.4375 - F1: 0.4000
sub_14:Test (Best Model) - Loss: 3.3774 - Accuracy: 0.5000 - F1: 0.4921
sub_14:Test (Best Model) - Loss: 2.4998 - Accuracy: 0.4375 - F1: 0.4286
sub_14:Test (Best Model) - Loss: 2.8061 - Accuracy: 0.5312 - F1: 0.4684
sub_14:Test (Best Model) - Loss: 3.9885 - Accuracy: 0.5312 - F1: 0.5077
sub_14:Test (Best Model) - Loss: 5.0066 - Accuracy: 0.3750 - F1: 0.3725
sub_14:Test (Best Model) - Loss: 2.0800 - Accuracy: 0.5000 - F1: 0.4818
sub_15:Test (Best Model) - Loss: 3.8566 - Accuracy: 0.6562 - F1: 0.6390
sub_15:Test (Best Model) - Loss: 4.7883 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 3.5145 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 2.7526 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 5.2673 - Accuracy: 0.5625 - F1: 0.5625
sub_15:Test (Best Model) - Loss: 5.7001 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 5.8199 - Accuracy: 0.5312 - F1: 0.5271
sub_15:Test (Best Model) - Loss: 6.1552 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 4.4815 - Accuracy: 0.6250 - F1: 0.6000
sub_15:Test (Best Model) - Loss: 5.8028 - Accuracy: 0.5312 - F1: 0.5195
sub_15:Test (Best Model) - Loss: 2.1874 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 2.5140 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 2.3656 - Accuracy: 0.4688 - F1: 0.4640
sub_15:Test (Best Model) - Loss: 1.8465 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 2.9138 - Accuracy: 0.3750 - F1: 0.3725
sub_16:Test (Best Model) - Loss: 2.1241 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 1.6247 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 2.2413 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 2.4800 - Accuracy: 0.5625 - F1: 0.4589
sub_16:Test (Best Model) - Loss: 2.3877 - Accuracy: 0.4375 - F1: 0.4375
sub_16:Test (Best Model) - Loss: 2.9497 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 3.0957 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 2.0601 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 2.8929 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 4.5025 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 4.7791 - Accuracy: 0.5000 - F1: 0.4818
sub_16:Test (Best Model) - Loss: 2.9735 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 3.8073 - Accuracy: 0.5000 - F1: 0.4459
sub_16:Test (Best Model) - Loss: 3.4930 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 3.1643 - Accuracy: 0.4688 - F1: 0.4231
sub_17:Test (Best Model) - Loss: 3.7836 - Accuracy: 0.6061 - F1: 0.5815
sub_17:Test (Best Model) - Loss: 1.5598 - Accuracy: 0.5758 - F1: 0.5722
sub_17:Test (Best Model) - Loss: 2.6241 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 2.7411 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 2.6643 - Accuracy: 0.4242 - F1: 0.4157
sub_17:Test (Best Model) - Loss: 4.1323 - Accuracy: 0.4545 - F1: 0.4540
sub_17:Test (Best Model) - Loss: 2.9516 - Accuracy: 0.4848 - F1: 0.4672
sub_17:Test (Best Model) - Loss: 3.7422 - Accuracy: 0.5152 - F1: 0.5111
sub_17:Test (Best Model) - Loss: 2.8183 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 1.6397 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 2.2238 - Accuracy: 0.3750 - F1: 0.3750
sub_17:Test (Best Model) - Loss: 2.9207 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 3.8821 - Accuracy: 0.5312 - F1: 0.5077
sub_17:Test (Best Model) - Loss: 2.5772 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 3.5932 - Accuracy: 0.5312 - F1: 0.5077
sub_18:Test (Best Model) - Loss: 2.8934 - Accuracy: 0.6061 - F1: 0.6061
sub_18:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.7273 - F1: 0.7263
sub_18:Test (Best Model) - Loss: 1.9223 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 2.4523 - Accuracy: 0.5758 - F1: 0.5558
sub_18:Test (Best Model) - Loss: 2.6008 - Accuracy: 0.6364 - F1: 0.6360
sub_18:Test (Best Model) - Loss: 3.4163 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 3.5318 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 3.8818 - Accuracy: 0.5625 - F1: 0.5625
sub_18:Test (Best Model) - Loss: 3.1727 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 3.4091 - Accuracy: 0.5000 - F1: 0.5000
sub_18:Test (Best Model) - Loss: 1.8178 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 4.7028 - Accuracy: 0.5625 - F1: 0.5556
sub_18:Test (Best Model) - Loss: 1.7967 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 2.9319 - Accuracy: 0.5000 - F1: 0.4921
sub_18:Test (Best Model) - Loss: 2.6785 - Accuracy: 0.5000 - F1: 0.4980
sub_19:Test (Best Model) - Loss: 4.6523 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 2.4301 - Accuracy: 0.4062 - F1: 0.3764
sub_19:Test (Best Model) - Loss: 1.8614 - Accuracy: 0.5000 - F1: 0.4459
sub_19:Test (Best Model) - Loss: 6.9484 - Accuracy: 0.3438 - F1: 0.2558
sub_19:Test (Best Model) - Loss: 3.0618 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 3.6149 - Accuracy: 0.4375 - F1: 0.4170
sub_19:Test (Best Model) - Loss: 4.8169 - Accuracy: 0.2500 - F1: 0.2227
sub_19:Test (Best Model) - Loss: 5.7416 - Accuracy: 0.3438 - F1: 0.3108
sub_19:Test (Best Model) - Loss: 6.0488 - Accuracy: 0.3438 - F1: 0.3273
sub_19:Test (Best Model) - Loss: 6.1331 - Accuracy: 0.2188 - F1: 0.2180
sub_19:Test (Best Model) - Loss: 3.3534 - Accuracy: 0.5000 - F1: 0.4921
sub_19:Test (Best Model) - Loss: 2.9320 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 1.9655 - Accuracy: 0.6250 - F1: 0.6250
sub_19:Test (Best Model) - Loss: 2.5315 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 2.2097 - Accuracy: 0.5000 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 2.7372 - Accuracy: 0.5625 - F1: 0.4909
sub_20:Test (Best Model) - Loss: 2.6979 - Accuracy: 0.6562 - F1: 0.6267
sub_20:Test (Best Model) - Loss: 3.8688 - Accuracy: 0.6250 - F1: 0.5636
sub_20:Test (Best Model) - Loss: 4.4405 - Accuracy: 0.5312 - F1: 0.3992
sub_20:Test (Best Model) - Loss: 5.3145 - Accuracy: 0.5000 - F1: 0.4182
sub_20:Test (Best Model) - Loss: 3.5619 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 2.2214 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 4.3339 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 3.4262 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 3.1247 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 7.3134 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 5.6193 - Accuracy: 0.4848 - F1: 0.4772
sub_20:Test (Best Model) - Loss: 3.9084 - Accuracy: 0.6364 - F1: 0.6333
sub_20:Test (Best Model) - Loss: 7.3109 - Accuracy: 0.4848 - F1: 0.4772
sub_20:Test (Best Model) - Loss: 4.6289 - Accuracy: 0.5758 - F1: 0.5558
sub_21:Test (Best Model) - Loss: 3.8731 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 4.6273 - Accuracy: 0.2812 - F1: 0.2633
sub_21:Test (Best Model) - Loss: 4.0922 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 3.4970 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 4.7893 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 2.8590 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 2.8012 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 3.7151 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 3.2548 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 3.5897 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 5.6681 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 2.2156 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 5.0095 - Accuracy: 0.2812 - F1: 0.2633
sub_21:Test (Best Model) - Loss: 2.9258 - Accuracy: 0.3125 - F1: 0.3016
sub_21:Test (Best Model) - Loss: 3.2793 - Accuracy: 0.6562 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 3.2862 - Accuracy: 0.4375 - F1: 0.4375
sub_22:Test (Best Model) - Loss: 2.0180 - Accuracy: 0.5625 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 2.6799 - Accuracy: 0.5000 - F1: 0.4980
sub_22:Test (Best Model) - Loss: 1.9640 - Accuracy: 0.5625 - F1: 0.4909
sub_22:Test (Best Model) - Loss: 2.3341 - Accuracy: 0.6562 - F1: 0.6476
sub_22:Test (Best Model) - Loss: 3.1626 - Accuracy: 0.5455 - F1: 0.5387
sub_22:Test (Best Model) - Loss: 2.6273 - Accuracy: 0.6061 - F1: 0.5196
sub_22:Test (Best Model) - Loss: 3.2540 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 3.5540 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 3.0934 - Accuracy: 0.5152 - F1: 0.4545
sub_22:Test (Best Model) - Loss: 2.9391 - Accuracy: 0.5938 - F1: 0.5901
sub_22:Test (Best Model) - Loss: 3.1901 - Accuracy: 0.4375 - F1: 0.4353
sub_22:Test (Best Model) - Loss: 3.3006 - Accuracy: 0.3750 - F1: 0.3333
sub_22:Test (Best Model) - Loss: 2.4673 - Accuracy: 0.5312 - F1: 0.5077
sub_22:Test (Best Model) - Loss: 2.8658 - Accuracy: 0.6250 - F1: 0.6250
sub_23:Test (Best Model) - Loss: 2.8910 - Accuracy: 0.6061 - F1: 0.5926
sub_23:Test (Best Model) - Loss: 3.3778 - Accuracy: 0.6061 - F1: 0.5460
sub_23:Test (Best Model) - Loss: 3.0538 - Accuracy: 0.5152 - F1: 0.4762
sub_23:Test (Best Model) - Loss: 2.3207 - Accuracy: 0.4848 - F1: 0.4063
sub_23:Test (Best Model) - Loss: 3.1256 - Accuracy: 0.6061 - F1: 0.5926
sub_23:Test (Best Model) - Loss: 3.8429 - Accuracy: 0.5000 - F1: 0.4980
sub_23:Test (Best Model) - Loss: 3.0634 - Accuracy: 0.5625 - F1: 0.5625
sub_23:Test (Best Model) - Loss: 2.4798 - Accuracy: 0.6250 - F1: 0.6250
sub_23:Test (Best Model) - Loss: 1.7566 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 3.8936 - Accuracy: 0.4688 - F1: 0.4682
sub_23:Test (Best Model) - Loss: 4.9125 - Accuracy: 0.5152 - F1: 0.4923
sub_23:Test (Best Model) - Loss: 3.2201 - Accuracy: 0.6061 - F1: 0.5662
sub_23:Test (Best Model) - Loss: 4.7953 - Accuracy: 0.4848 - F1: 0.4672
sub_23:Test (Best Model) - Loss: 4.4467 - Accuracy: 0.5758 - F1: 0.4978
sub_23:Test (Best Model) - Loss: 4.2950 - Accuracy: 0.5455 - F1: 0.4457
sub_24:Test (Best Model) - Loss: 2.2070 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 3.2076 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 1.9899 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 2.2012 - Accuracy: 0.5000 - F1: 0.4667
sub_24:Test (Best Model) - Loss: 2.7402 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 2.8783 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 2.3840 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 1.7564 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 2.0212 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 1.3484 - Accuracy: 0.6562 - F1: 0.6532
sub_24:Test (Best Model) - Loss: 3.1280 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 2.7418 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 3.6606 - Accuracy: 0.3125 - F1: 0.3098
sub_24:Test (Best Model) - Loss: 3.6490 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 3.3412 - Accuracy: 0.5000 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 3.4898 - Accuracy: 0.3939 - F1: 0.2826
sub_25:Test (Best Model) - Loss: 3.2082 - Accuracy: 0.4545 - F1: 0.4417
sub_25:Test (Best Model) - Loss: 4.7724 - Accuracy: 0.5455 - F1: 0.5455
sub_25:Test (Best Model) - Loss: 5.2750 - Accuracy: 0.4242 - F1: 0.3660
sub_25:Test (Best Model) - Loss: 3.4598 - Accuracy: 0.4848 - F1: 0.4328
sub_25:Test (Best Model) - Loss: 2.8123 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.5938 - F1: 0.5589
sub_25:Test (Best Model) - Loss: 3.3185 - Accuracy: 0.6250 - F1: 0.6250
sub_25:Test (Best Model) - Loss: 2.3430 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 2.4016 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 2.5952 - Accuracy: 0.6875 - F1: 0.6761
sub_25:Test (Best Model) - Loss: 3.3069 - Accuracy: 0.5312 - F1: 0.5077
sub_25:Test (Best Model) - Loss: 2.2058 - Accuracy: 0.6562 - F1: 0.6390
sub_25:Test (Best Model) - Loss: 4.5602 - Accuracy: 0.5625 - F1: 0.4589
sub_25:Test (Best Model) - Loss: 3.7294 - Accuracy: 0.5312 - F1: 0.5077
sub_26:Test (Best Model) - Loss: 4.1722 - Accuracy: 0.5152 - F1: 0.5111
sub_26:Test (Best Model) - Loss: 6.8334 - Accuracy: 0.4848 - F1: 0.4672
sub_26:Test (Best Model) - Loss: 3.1420 - Accuracy: 0.5152 - F1: 0.5038
sub_26:Test (Best Model) - Loss: 2.0033 - Accuracy: 0.6364 - F1: 0.6192
sub_26:Test (Best Model) - Loss: 2.2332 - Accuracy: 0.5758 - F1: 0.5558
sub_26:Test (Best Model) - Loss: 2.9609 - Accuracy: 0.5312 - F1: 0.5077
sub_26:Test (Best Model) - Loss: 2.7052 - Accuracy: 0.5625 - F1: 0.5608
sub_26:Test (Best Model) - Loss: 3.3487 - Accuracy: 0.4688 - F1: 0.4640
sub_26:Test (Best Model) - Loss: 2.6936 - Accuracy: 0.6875 - F1: 0.6667
sub_26:Test (Best Model) - Loss: 2.5675 - Accuracy: 0.7500 - F1: 0.7409
sub_26:Test (Best Model) - Loss: 2.2853 - Accuracy: 0.6250 - F1: 0.6190
sub_26:Test (Best Model) - Loss: 2.4750 - Accuracy: 0.6250 - F1: 0.6113
sub_26:Test (Best Model) - Loss: 3.5298 - Accuracy: 0.5000 - F1: 0.4818
sub_26:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.6250 - F1: 0.6113
sub_26:Test (Best Model) - Loss: 0.9378 - Accuracy: 0.6875 - F1: 0.6761
sub_27:Test (Best Model) - Loss: 3.7836 - Accuracy: 0.6061 - F1: 0.5815
sub_27:Test (Best Model) - Loss: 1.5598 - Accuracy: 0.5758 - F1: 0.5722
sub_27:Test (Best Model) - Loss: 2.6241 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 2.7411 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 2.6643 - Accuracy: 0.4242 - F1: 0.4157
sub_27:Test (Best Model) - Loss: 4.1323 - Accuracy: 0.4545 - F1: 0.4540
sub_27:Test (Best Model) - Loss: 2.9516 - Accuracy: 0.4848 - F1: 0.4672
sub_27:Test (Best Model) - Loss: 3.7422 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 2.8183 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 1.6397 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 2.2238 - Accuracy: 0.3750 - F1: 0.3750
sub_27:Test (Best Model) - Loss: 2.9207 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 3.8821 - Accuracy: 0.5312 - F1: 0.5077
sub_27:Test (Best Model) - Loss: 2.5772 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 3.5932 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 1.0848 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 2.1446 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 1.8702 - Accuracy: 0.4062 - F1: 0.4057
sub_28:Test (Best Model) - Loss: 2.5535 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 3.1795 - Accuracy: 0.3438 - F1: 0.3431
sub_28:Test (Best Model) - Loss: 4.6589 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 4.4738 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 6.6538 - Accuracy: 0.4375 - F1: 0.4000
sub_28:Test (Best Model) - Loss: 3.8723 - Accuracy: 0.5625 - F1: 0.5152
sub_28:Test (Best Model) - Loss: 7.0465 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 3.9039 - Accuracy: 0.5938 - F1: 0.5733
sub_28:Test (Best Model) - Loss: 2.2482 - Accuracy: 0.2812 - F1: 0.2451
sub_28:Test (Best Model) - Loss: 1.8891 - Accuracy: 0.5938 - F1: 0.5733
sub_28:Test (Best Model) - Loss: 1.2829 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 2.0598 - Accuracy: 0.4375 - F1: 0.4353
sub_29:Test (Best Model) - Loss: 2.3737 - Accuracy: 0.7500 - F1: 0.7333
sub_29:Test (Best Model) - Loss: 4.5822 - Accuracy: 0.5000 - F1: 0.4921
sub_29:Test (Best Model) - Loss: 2.1511 - Accuracy: 0.6562 - F1: 0.6390
sub_29:Test (Best Model) - Loss: 2.9110 - Accuracy: 0.7188 - F1: 0.6811
sub_29:Test (Best Model) - Loss: 3.5319 - Accuracy: 0.6250 - F1: 0.5362
sub_29:Test (Best Model) - Loss: 3.1968 - Accuracy: 0.5000 - F1: 0.4667
sub_29:Test (Best Model) - Loss: 2.2274 - Accuracy: 0.6250 - F1: 0.6000
sub_29:Test (Best Model) - Loss: 1.8404 - Accuracy: 0.5625 - F1: 0.5466
sub_29:Test (Best Model) - Loss: 3.1799 - Accuracy: 0.6250 - F1: 0.6000
sub_29:Test (Best Model) - Loss: 4.4192 - Accuracy: 0.5938 - F1: 0.5135
sub_29:Test (Best Model) - Loss: 3.0951 - Accuracy: 0.6667 - F1: 0.6667
sub_29:Test (Best Model) - Loss: 2.2040 - Accuracy: 0.6061 - F1: 0.6061
sub_29:Test (Best Model) - Loss: 3.1293 - Accuracy: 0.6061 - F1: 0.6046
sub_29:Test (Best Model) - Loss: 2.0275 - Accuracy: 0.6667 - F1: 0.6617
sub_29:Test (Best Model) - Loss: 4.1226 - Accuracy: 0.5758 - F1: 0.5754

=== Summary Results ===

acc: 53.38 ± 5.43
F1: 51.33 ± 5.53
acc-in: 61.08 ± 4.69
F1-in: 58.45 ± 5.13
