lr: 1e-06
sub_26:Test (Best Model) - Loss: 0.2628 - Accuracy: 0.9394 - F1: 0.9393
sub_16:Test (Best Model) - Loss: 0.4348 - Accuracy: 0.7812 - F1: 0.7810
sub_14:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.5000 - F1: 0.4182
sub_7:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.5625 - F1: 0.5152
sub_28:Test (Best Model) - Loss: 0.3252 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.2303 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.3377 - Accuracy: 0.9062 - F1: 0.9062
sub_9:Test (Best Model) - Loss: 0.2311 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.3819 - Accuracy: 0.8788 - F1: 0.8787
sub_5:Test (Best Model) - Loss: 0.4951 - Accuracy: 0.7812 - F1: 0.7793
sub_8:Test (Best Model) - Loss: 0.3702 - Accuracy: 0.9062 - F1: 0.9062
sub_11:Test (Best Model) - Loss: 0.5840 - Accuracy: 0.6667 - F1: 0.6654
sub_1:Test (Best Model) - Loss: 0.2853 - Accuracy: 0.9688 - F1: 0.9685
sub_19:Test (Best Model) - Loss: 0.3267 - Accuracy: 0.8438 - F1: 0.8424
sub_23:Test (Best Model) - Loss: 0.1580 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.2024 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1841 - Accuracy: 0.9688 - F1: 0.9680
sub_6:Test (Best Model) - Loss: 0.5414 - Accuracy: 0.5938 - F1: 0.5836
sub_21:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.6875 - F1: 0.6863
sub_17:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.5758 - F1: 0.5722
sub_27:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.5758 - F1: 0.5722
sub_15:Test (Best Model) - Loss: 0.1903 - Accuracy: 0.9375 - F1: 0.9352
sub_4:Test (Best Model) - Loss: 0.1986 - Accuracy: 0.9697 - F1: 0.9692
sub_25:Test (Best Model) - Loss: 0.3780 - Accuracy: 0.9091 - F1: 0.9088
sub_10:Test (Best Model) - Loss: 0.2452 - Accuracy: 0.9375 - F1: 0.9373
sub_3:Test (Best Model) - Loss: 0.7979 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 0.3627 - Accuracy: 0.8750 - F1: 0.8745
sub_2:Test (Best Model) - Loss: 0.7584 - Accuracy: 0.4848 - F1: 0.4672
sub_20:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.5938 - F1: 0.5589
sub_12:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.7812 - F1: 0.7793
sub_26:Test (Best Model) - Loss: 0.4974 - Accuracy: 0.6667 - F1: 0.6654
sub_14:Test (Best Model) - Loss: 0.8543 - Accuracy: 0.3125 - F1: 0.3098
sub_28:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.1875 - F1: 0.1875
sub_7:Test (Best Model) - Loss: 0.5063 - Accuracy: 0.7812 - F1: 0.7625
sub_8:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.5938 - F1: 0.5393
sub_11:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6061 - F1: 0.6002
sub_16:Test (Best Model) - Loss: 0.4482 - Accuracy: 0.7812 - F1: 0.7758
sub_9:Test (Best Model) - Loss: 0.7598 - Accuracy: 0.5312 - F1: 0.5271
sub_4:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.5455 - F1: 0.5455
sub_22:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.6562 - F1: 0.6267
sub_18:Test (Best Model) - Loss: 0.2279 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.6087 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.9818 - Accuracy: 0.3125 - F1: 0.2874
sub_1:Test (Best Model) - Loss: 0.3472 - Accuracy: 0.8438 - F1: 0.8436
sub_20:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.6562 - F1: 0.6102
sub_3:Test (Best Model) - Loss: 0.5317 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.4285 - Accuracy: 0.8788 - F1: 0.8759
sub_19:Test (Best Model) - Loss: 0.4109 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.5938 - F1: 0.5836
sub_29:Test (Best Model) - Loss: 0.4419 - Accuracy: 0.8125 - F1: 0.8125
sub_10:Test (Best Model) - Loss: 0.5125 - Accuracy: 0.7500 - F1: 0.7333
sub_21:Test (Best Model) - Loss: 1.1000 - Accuracy: 0.2500 - F1: 0.2500
sub_15:Test (Best Model) - Loss: 0.2932 - Accuracy: 0.9375 - F1: 0.9365
sub_2:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5455 - F1: 0.5455
sub_18:Test (Best Model) - Loss: 0.3687 - Accuracy: 0.8485 - F1: 0.8433
sub_4:Test (Best Model) - Loss: 0.4990 - Accuracy: 0.7879 - F1: 0.7847
sub_28:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.7500 - F1: 0.7409
sub_6:Test (Best Model) - Loss: 0.5345 - Accuracy: 0.8438 - F1: 0.8398
sub_24:Test (Best Model) - Loss: 0.5424 - Accuracy: 0.8125 - F1: 0.8118
sub_20:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.8323 - Accuracy: 0.5312 - F1: 0.5077
sub_12:Test (Best Model) - Loss: 0.3300 - Accuracy: 0.9062 - F1: 0.9054
sub_17:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.5455 - F1: 0.5387
sub_29:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.7862 - Accuracy: 0.4688 - F1: 0.3976
sub_13:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.4062 - F1: 0.2889
sub_9:Test (Best Model) - Loss: 0.7972 - Accuracy: 0.4688 - F1: 0.4640
sub_25:Test (Best Model) - Loss: 0.3571 - Accuracy: 0.7879 - F1: 0.7746
sub_8:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5312 - F1: 0.5195
sub_22:Test (Best Model) - Loss: 0.3848 - Accuracy: 0.8125 - F1: 0.7922
sub_24:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.1779 - Accuracy: 0.9697 - F1: 0.9692
sub_7:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.6875 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 0.3679 - Accuracy: 0.8750 - F1: 0.8704
sub_5:Test (Best Model) - Loss: 0.8346 - Accuracy: 0.4688 - F1: 0.3637
sub_11:Test (Best Model) - Loss: 0.4524 - Accuracy: 0.8788 - F1: 0.8787
sub_13:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.6250 - F1: 0.5636
sub_4:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.6667 - F1: 0.6159
sub_19:Test (Best Model) - Loss: 0.5329 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.7188 - F1: 0.6632
sub_6:Test (Best Model) - Loss: 0.4565 - Accuracy: 0.7500 - F1: 0.7333
sub_21:Test (Best Model) - Loss: 0.5237 - Accuracy: 0.7188 - F1: 0.6632
sub_3:Test (Best Model) - Loss: 0.5048 - Accuracy: 0.7188 - F1: 0.6946
sub_16:Test (Best Model) - Loss: 0.2933 - Accuracy: 0.9062 - F1: 0.9015
sub_14:Test (Best Model) - Loss: 0.4379 - Accuracy: 0.9375 - F1: 0.9373
sub_24:Test (Best Model) - Loss: 0.5500 - Accuracy: 0.6562 - F1: 0.5883
sub_27:Test (Best Model) - Loss: 0.2791 - Accuracy: 0.9394 - F1: 0.9389
sub_1:Test (Best Model) - Loss: 0.4282 - Accuracy: 0.8438 - F1: 0.8398
sub_17:Test (Best Model) - Loss: 0.2791 - Accuracy: 0.9394 - F1: 0.9389
sub_20:Test (Best Model) - Loss: 0.9909 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.2083 - Accuracy: 0.9394 - F1: 0.9380
sub_10:Test (Best Model) - Loss: 0.7477 - Accuracy: 0.5938 - F1: 0.4340
sub_2:Test (Best Model) - Loss: 0.4695 - Accuracy: 0.7576 - F1: 0.7519
sub_5:Test (Best Model) - Loss: 0.8338 - Accuracy: 0.4062 - F1: 0.4057
sub_13:Test (Best Model) - Loss: 1.4765 - Accuracy: 0.3750 - F1: 0.2727
sub_11:Test (Best Model) - Loss: 0.5137 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.3824 - Accuracy: 0.7879 - F1: 0.7664
sub_7:Test (Best Model) - Loss: 0.3031 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.5312 - F1: 0.4910
sub_28:Test (Best Model) - Loss: 0.4797 - Accuracy: 0.7812 - F1: 0.7519
sub_3:Test (Best Model) - Loss: 0.4307 - Accuracy: 0.8750 - F1: 0.8745
sub_19:Test (Best Model) - Loss: 0.4124 - Accuracy: 0.8125 - F1: 0.7922
sub_6:Test (Best Model) - Loss: 0.8173 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.7582 - Accuracy: 0.5000 - F1: 0.4459
sub_12:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.4062 - F1: 0.2889
sub_9:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.8438 - F1: 0.8303
sub_24:Test (Best Model) - Loss: 1.6754 - Accuracy: 0.3750 - F1: 0.2727
sub_26:Test (Best Model) - Loss: 0.9937 - Accuracy: 0.5152 - F1: 0.4261
sub_29:Test (Best Model) - Loss: 0.4368 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 1.4659 - Accuracy: 0.4062 - F1: 0.2889
sub_22:Test (Best Model) - Loss: 0.2795 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 1.1307 - Accuracy: 0.4242 - F1: 0.2979
sub_20:Test (Best Model) - Loss: 0.4984 - Accuracy: 0.8125 - F1: 0.8118
sub_2:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.7879 - F1: 0.7664
sub_25:Test (Best Model) - Loss: 0.3105 - Accuracy: 0.8788 - F1: 0.8778
sub_5:Test (Best Model) - Loss: 2.0546 - Accuracy: 0.4062 - F1: 0.2889
sub_4:Test (Best Model) - Loss: 1.3497 - Accuracy: 0.4545 - F1: 0.3543
sub_23:Test (Best Model) - Loss: 0.5306 - Accuracy: 0.7576 - F1: 0.7574
sub_19:Test (Best Model) - Loss: 1.8414 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.2645 - Accuracy: 0.9375 - F1: 0.9352
sub_11:Test (Best Model) - Loss: 1.9217 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 1.2827 - Accuracy: 0.4062 - F1: 0.2889
sub_8:Test (Best Model) - Loss: 1.7079 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.4062 - F1: 0.2889
sub_12:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.6250 - F1: 0.5362
sub_10:Test (Best Model) - Loss: 0.9543 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 1.2575 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 1.9549 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.3924 - Accuracy: 0.9091 - F1: 0.9060
sub_9:Test (Best Model) - Loss: 1.1236 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.3924 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.4212 - Accuracy: 0.7500 - F1: 0.7091
sub_22:Test (Best Model) - Loss: 1.4019 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 1.4969 - Accuracy: 0.4062 - F1: 0.2889
sub_13:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.4242 - F1: 0.2979
sub_2:Test (Best Model) - Loss: 1.7710 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 2.3715 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 1.6526 - Accuracy: 0.4242 - F1: 0.2979
sub_15:Test (Best Model) - Loss: 0.7749 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.9506 - Accuracy: 0.4062 - F1: 0.3764
sub_17:Test (Best Model) - Loss: 1.5647 - Accuracy: 0.4242 - F1: 0.2979
sub_20:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.1875 - F1: 0.1746
sub_11:Test (Best Model) - Loss: 0.7382 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 1.5647 - Accuracy: 0.4242 - F1: 0.2979
sub_14:Test (Best Model) - Loss: 0.3776 - Accuracy: 0.8438 - F1: 0.8303
sub_6:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6667 - F1: 0.6667
sub_5:Test (Best Model) - Loss: 0.3965 - Accuracy: 0.9062 - F1: 0.9015
sub_16:Test (Best Model) - Loss: 0.4788 - Accuracy: 0.7812 - F1: 0.7519
sub_10:Test (Best Model) - Loss: 0.4143 - Accuracy: 0.8438 - F1: 0.8398
sub_4:Test (Best Model) - Loss: 0.4102 - Accuracy: 0.8485 - F1: 0.8479
sub_26:Test (Best Model) - Loss: 0.4165 - Accuracy: 0.8438 - F1: 0.8398
sub_19:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.7500 - F1: 0.7091
sub_21:Test (Best Model) - Loss: 0.5293 - Accuracy: 0.6875 - F1: 0.6825
sub_8:Test (Best Model) - Loss: 0.5254 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.4372 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 1.0210 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.2697 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 1.5296 - Accuracy: 0.4062 - F1: 0.3552
sub_7:Test (Best Model) - Loss: 0.5067 - Accuracy: 0.7812 - F1: 0.7810
sub_6:Test (Best Model) - Loss: 0.9852 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.4301 - Accuracy: 0.8125 - F1: 0.8000
sub_5:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 0.4507 - Accuracy: 0.7879 - F1: 0.7664
sub_10:Test (Best Model) - Loss: 0.8777 - Accuracy: 0.5938 - F1: 0.4340
sub_20:Test (Best Model) - Loss: 0.3277 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.5453 - Accuracy: 0.7188 - F1: 0.7046
sub_23:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.5938 - F1: 0.4793
sub_22:Test (Best Model) - Loss: 0.3282 - Accuracy: 0.9394 - F1: 0.9389
sub_28:Test (Best Model) - Loss: 0.9861 - Accuracy: 0.5938 - F1: 0.5589
sub_29:Test (Best Model) - Loss: 0.3597 - Accuracy: 0.9062 - F1: 0.9062
sub_15:Test (Best Model) - Loss: 0.4124 - Accuracy: 0.8438 - F1: 0.8436
sub_13:Test (Best Model) - Loss: 0.8703 - Accuracy: 0.3030 - F1: 0.3005
sub_21:Test (Best Model) - Loss: 0.8547 - Accuracy: 0.4688 - F1: 0.4682
sub_3:Test (Best Model) - Loss: 1.1306 - Accuracy: 0.4242 - F1: 0.4157
sub_18:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.6562 - F1: 0.6559
sub_24:Test (Best Model) - Loss: 1.2025 - Accuracy: 0.2500 - F1: 0.2000
sub_17:Test (Best Model) - Loss: 0.8585 - Accuracy: 0.5455 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.8585 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.9901 - Accuracy: 0.5455 - F1: 0.4058
sub_20:Test (Best Model) - Loss: 0.9512 - Accuracy: 0.5000 - F1: 0.4182
sub_9:Test (Best Model) - Loss: 0.4690 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 0.5796 - Accuracy: 0.7188 - F1: 0.6632
sub_2:Test (Best Model) - Loss: 0.9529 - Accuracy: 0.5000 - F1: 0.3333
sub_16:Test (Best Model) - Loss: 0.8415 - Accuracy: 0.5312 - F1: 0.4386
sub_5:Test (Best Model) - Loss: 0.4371 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.7435 - Accuracy: 0.5758 - F1: 0.4653
sub_26:Test (Best Model) - Loss: 0.3760 - Accuracy: 0.8438 - F1: 0.8424
sub_1:Test (Best Model) - Loss: 0.3075 - Accuracy: 0.9091 - F1: 0.9091
sub_29:Test (Best Model) - Loss: 0.9503 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 1.0838 - Accuracy: 0.3636 - F1: 0.3239
sub_19:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.4796 - Accuracy: 0.7500 - F1: 0.7091
sub_10:Test (Best Model) - Loss: 0.8884 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.3854 - Accuracy: 0.8788 - F1: 0.8731
sub_4:Test (Best Model) - Loss: 0.8598 - Accuracy: 0.5152 - F1: 0.3400
sub_23:Test (Best Model) - Loss: 1.1160 - Accuracy: 0.2500 - F1: 0.2471
sub_20:Test (Best Model) - Loss: 1.1431 - Accuracy: 0.4062 - F1: 0.2889
sub_14:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 1.0246 - Accuracy: 0.4848 - F1: 0.4063
sub_28:Test (Best Model) - Loss: 0.4864 - Accuracy: 0.8125 - F1: 0.7922
sub_16:Test (Best Model) - Loss: 0.5960 - Accuracy: 0.6250 - F1: 0.6190
sub_21:Test (Best Model) - Loss: 1.0107 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.4691 - Accuracy: 0.7812 - F1: 0.7793
sub_5:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.5312 - F1: 0.4684
sub_13:Test (Best Model) - Loss: 0.8846 - Accuracy: 0.4242 - F1: 0.2979
sub_18:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.6562 - F1: 0.6267
sub_15:Test (Best Model) - Loss: 0.9525 - Accuracy: 0.4062 - F1: 0.3914
sub_9:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.6250 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.5321 - Accuracy: 0.5455 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 0.9043 - Accuracy: 0.4848 - F1: 0.4328
sub_2:Test (Best Model) - Loss: 0.8610 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 0.7507 - Accuracy: 0.5455 - F1: 0.4995
sub_10:Test (Best Model) - Loss: 0.9190 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.4858 - Accuracy: 0.7188 - F1: 0.7163
sub_19:Test (Best Model) - Loss: 0.4112 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.7507 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.9623 - Accuracy: 0.3030 - F1: 0.3030
sub_8:Test (Best Model) - Loss: 1.5462 - Accuracy: 0.3750 - F1: 0.2727
sub_29:Test (Best Model) - Loss: 0.2405 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.9640 - Accuracy: 0.4242 - F1: 0.3365
sub_22:Test (Best Model) - Loss: 0.4903 - Accuracy: 0.7273 - F1: 0.7263
sub_12:Test (Best Model) - Loss: 0.5927 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.2795 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.4117 - Accuracy: 0.8750 - F1: 0.8750
sub_3:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.4688 - F1: 0.3637
sub_25:Test (Best Model) - Loss: 0.3637 - Accuracy: 0.8750 - F1: 0.8750
sub_24:Test (Best Model) - Loss: 0.5248 - Accuracy: 0.8438 - F1: 0.8303
sub_16:Test (Best Model) - Loss: 0.9415 - Accuracy: 0.3750 - F1: 0.2727
sub_7:Test (Best Model) - Loss: 0.5869 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.5372 - Accuracy: 0.6562 - F1: 0.6390
sub_26:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.5000 - F1: 0.4182
sub_5:Test (Best Model) - Loss: 0.8477 - Accuracy: 0.5000 - F1: 0.4182
sub_22:Test (Best Model) - Loss: 1.5631 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.4074 - Accuracy: 0.7812 - F1: 0.7793
sub_12:Test (Best Model) - Loss: 0.5506 - Accuracy: 0.6970 - F1: 0.6898
sub_13:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.7273 - F1: 0.6857
sub_18:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.2661 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.6970 - F1: 0.6967
sub_20:Test (Best Model) - Loss: 0.7488 - Accuracy: 0.4848 - F1: 0.4527
sub_27:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.6970 - F1: 0.6967
sub_10:Test (Best Model) - Loss: 0.7640 - Accuracy: 0.5312 - F1: 0.5195
sub_3:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 1.0006 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 0.2650 - Accuracy: 0.9688 - F1: 0.9680
sub_9:Test (Best Model) - Loss: 0.4092 - Accuracy: 0.7812 - F1: 0.7793
sub_16:Test (Best Model) - Loss: 1.0340 - Accuracy: 0.5000 - F1: 0.4182
sub_6:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.6667 - F1: 0.6617
sub_8:Test (Best Model) - Loss: 0.5278 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.3857 - Accuracy: 0.8750 - F1: 0.8730
sub_12:Test (Best Model) - Loss: 1.2258 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 1.6221 - Accuracy: 0.4688 - F1: 0.3637
sub_15:Test (Best Model) - Loss: 0.2405 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 1.0354 - Accuracy: 0.4242 - F1: 0.2979
sub_13:Test (Best Model) - Loss: 1.0267 - Accuracy: 0.3030 - F1: 0.2595
sub_2:Test (Best Model) - Loss: 0.5658 - Accuracy: 0.6875 - F1: 0.6863
sub_17:Test (Best Model) - Loss: 0.9505 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.8182 - F1: 0.8180
sub_27:Test (Best Model) - Loss: 0.9505 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.3173 - Accuracy: 0.8750 - F1: 0.8750
sub_9:Test (Best Model) - Loss: 0.5447 - Accuracy: 0.7812 - F1: 0.7810
sub_28:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.8779 - Accuracy: 0.5455 - F1: 0.4995
sub_7:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.4459
sub_19:Test (Best Model) - Loss: 0.5099 - Accuracy: 0.7812 - F1: 0.7810
sub_12:Test (Best Model) - Loss: 1.0216 - Accuracy: 0.4545 - F1: 0.3543
sub_23:Test (Best Model) - Loss: 0.9759 - Accuracy: 0.4688 - F1: 0.3976
sub_26:Test (Best Model) - Loss: 0.7878 - Accuracy: 0.4688 - F1: 0.3637
sub_24:Test (Best Model) - Loss: 0.7639 - Accuracy: 0.6250 - F1: 0.6000
sub_13:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.4062 - F1: 0.2889
sub_2:Test (Best Model) - Loss: 0.5726 - Accuracy: 0.6667 - F1: 0.6553
sub_10:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.6061 - F1: 0.6002
sub_18:Test (Best Model) - Loss: 0.7543 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 1.3184 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.5046 - Accuracy: 0.6562 - F1: 0.5594
sub_11:Test (Best Model) - Loss: 0.5068 - Accuracy: 0.7576 - F1: 0.7556
sub_5:Test (Best Model) - Loss: 0.7375 - Accuracy: 0.5312 - F1: 0.4684
sub_17:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.5758 - F1: 0.5227
sub_3:Test (Best Model) - Loss: 0.2514 - Accuracy: 0.9394 - F1: 0.9380
sub_27:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.5758 - F1: 0.5227
sub_7:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.6053 - Accuracy: 0.6562 - F1: 0.6476
sub_1:Test (Best Model) - Loss: 0.9502 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.5205 - Accuracy: 0.8182 - F1: 0.8096
sub_13:Test (Best Model) - Loss: 0.7658 - Accuracy: 0.4688 - F1: 0.3637
sub_2:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4848 - F1: 0.4829
sub_6:Test (Best Model) - Loss: 0.3579 - Accuracy: 0.8788 - F1: 0.8731
sub_8:Test (Best Model) - Loss: 0.4782 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.5619 - Accuracy: 0.7500 - F1: 0.7460
sub_21:Test (Best Model) - Loss: 0.5466 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.7844 - Accuracy: 0.5000 - F1: 0.4182
sub_9:Test (Best Model) - Loss: 0.1591 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.7456 - Accuracy: 0.5938 - F1: 0.5901
sub_11:Test (Best Model) - Loss: 0.4864 - Accuracy: 0.7576 - F1: 0.7574
sub_1:Test (Best Model) - Loss: 1.6544 - Accuracy: 0.2727 - F1: 0.2143
sub_13:Test (Best Model) - Loss: 1.0981 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.8922 - Accuracy: 0.3438 - F1: 0.3431
sub_24:Test (Best Model) - Loss: 0.9119 - Accuracy: 0.5000 - F1: 0.4667
sub_3:Test (Best Model) - Loss: 1.2065 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 0.4391 - Accuracy: 0.8182 - F1: 0.8180
sub_10:Test (Best Model) - Loss: 0.4961 - Accuracy: 0.7576 - F1: 0.7574
sub_20:Test (Best Model) - Loss: 0.7621 - Accuracy: 0.5758 - F1: 0.4225
sub_4:Test (Best Model) - Loss: 0.3924 - Accuracy: 0.8485 - F1: 0.8479
sub_2:Test (Best Model) - Loss: 0.9398 - Accuracy: 0.5152 - F1: 0.4923
sub_16:Test (Best Model) - Loss: 1.0854 - Accuracy: 0.2812 - F1: 0.2749
sub_12:Test (Best Model) - Loss: 0.7393 - Accuracy: 0.5312 - F1: 0.4684
sub_23:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.8788 - F1: 0.8787
sub_22:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.7500 - F1: 0.7490
sub_17:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.7812 - F1: 0.7810
sub_19:Test (Best Model) - Loss: 0.4783 - Accuracy: 0.8125 - F1: 0.8000
sub_5:Test (Best Model) - Loss: 0.8644 - Accuracy: 0.3438 - F1: 0.3379
sub_1:Test (Best Model) - Loss: 0.9845 - Accuracy: 0.4062 - F1: 0.2889
sub_27:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.7812 - F1: 0.7810
sub_20:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.6364 - F1: 0.5417
sub_15:Test (Best Model) - Loss: 0.4202 - Accuracy: 0.8125 - F1: 0.8118
sub_25:Test (Best Model) - Loss: 0.2811 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6667 - F1: 0.5935
sub_18:Test (Best Model) - Loss: 0.4893 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 0.9040 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.4056 - Accuracy: 0.7812 - F1: 0.7519
sub_16:Test (Best Model) - Loss: 1.0822 - Accuracy: 0.5312 - F1: 0.3469
sub_24:Test (Best Model) - Loss: 0.7864 - Accuracy: 0.5000 - F1: 0.4667
sub_6:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.6667 - F1: 0.5935
sub_28:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.6250 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.5538 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.8328 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 0.2337 - Accuracy: 0.9375 - F1: 0.9352
sub_11:Test (Best Model) - Loss: 0.4604 - Accuracy: 0.8485 - F1: 0.8433
sub_10:Test (Best Model) - Loss: 0.8783 - Accuracy: 0.5152 - F1: 0.3889
sub_21:Test (Best Model) - Loss: 0.8739 - Accuracy: 0.5312 - F1: 0.5195
sub_22:Test (Best Model) - Loss: 0.8199 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 1.2554 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 0.5571 - Accuracy: 0.6667 - F1: 0.6459
sub_28:Test (Best Model) - Loss: 0.7873 - Accuracy: 0.4688 - F1: 0.4231
sub_20:Test (Best Model) - Loss: 0.9350 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.5116 - Accuracy: 0.7500 - F1: 0.7091
sub_10:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6364 - F1: 0.5417
sub_23:Test (Best Model) - Loss: 0.9918 - Accuracy: 0.3636 - F1: 0.2667
sub_21:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.6250 - F1: 0.5000
sub_16:Test (Best Model) - Loss: 0.5827 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.3781 - Accuracy: 0.8125 - F1: 0.8118
sub_22:Test (Best Model) - Loss: 0.6162 - Accuracy: 0.6875 - F1: 0.6364
sub_14:Test (Best Model) - Loss: 1.0957 - Accuracy: 0.5625 - F1: 0.4167
sub_6:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.6970 - F1: 0.6413
sub_2:Test (Best Model) - Loss: 1.0051 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.4545 - Accuracy: 0.6667 - F1: 0.5935
sub_13:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.6875 - F1: 0.6667
sub_28:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.5938 - F1: 0.4793
sub_1:Test (Best Model) - Loss: 0.3851 - Accuracy: 0.8750 - F1: 0.8730
sub_8:Test (Best Model) - Loss: 0.6143 - Accuracy: 0.7812 - F1: 0.7703
sub_17:Test (Best Model) - Loss: 0.4422 - Accuracy: 0.8438 - F1: 0.8398
sub_5:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.5938 - F1: 0.5135
sub_18:Test (Best Model) - Loss: 0.3721 - Accuracy: 0.8750 - F1: 0.8745
sub_15:Test (Best Model) - Loss: 0.5383 - Accuracy: 0.6875 - F1: 0.6761
sub_26:Test (Best Model) - Loss: 0.2770 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.5289 - Accuracy: 0.7576 - F1: 0.7462
sub_9:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6562 - F1: 0.5883
sub_6:Test (Best Model) - Loss: 0.8854 - Accuracy: 0.4545 - F1: 0.4288
sub_27:Test (Best Model) - Loss: 0.4422 - Accuracy: 0.8438 - F1: 0.8398
sub_3:Test (Best Model) - Loss: 0.7475 - Accuracy: 0.6061 - F1: 0.4850
sub_24:Test (Best Model) - Loss: 0.5709 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6484 - Accuracy: 0.6250 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.2919 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.5661 - Accuracy: 0.8485 - F1: 0.8390
sub_19:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.8438 - F1: 0.8436
sub_12:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.7188 - F1: 0.6632
sub_7:Test (Best Model) - Loss: 0.7550 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.5938 - F1: 0.4793
sub_4:Test (Best Model) - Loss: 0.4868 - Accuracy: 0.8182 - F1: 0.8036
sub_25:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.7500 - F1: 0.7500
sub_26:Test (Best Model) - Loss: 0.3838 - Accuracy: 0.8125 - F1: 0.7922
sub_11:Test (Best Model) - Loss: 0.9964 - Accuracy: 0.3636 - F1: 0.3239
sub_28:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.5938 - F1: 0.4340
sub_22:Test (Best Model) - Loss: 0.7496 - Accuracy: 0.5312 - F1: 0.3992
sub_5:Test (Best Model) - Loss: 0.9648 - Accuracy: 0.5312 - F1: 0.3992
sub_18:Test (Best Model) - Loss: 0.2452 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.8206 - Accuracy: 0.5312 - F1: 0.3992
sub_12:Test (Best Model) - Loss: 1.1265 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 1.0706 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.4712 - Accuracy: 0.8125 - F1: 0.8057
sub_19:Test (Best Model) - Loss: 0.4656 - Accuracy: 0.8438 - F1: 0.8359
sub_26:Test (Best Model) - Loss: 0.8730 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.5625 - F1: 0.4909
sub_7:Test (Best Model) - Loss: 0.6056 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.6250 - F1: 0.5000
sub_27:Test (Best Model) - Loss: 0.4712 - Accuracy: 0.8125 - F1: 0.8057
sub_23:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.7273 - F1: 0.6857
sub_24:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5938 - F1: 0.4340
sub_29:Test (Best Model) - Loss: 0.7425 - Accuracy: 0.6364 - F1: 0.5909
sub_8:Test (Best Model) - Loss: 0.5393 - Accuracy: 0.6562 - F1: 0.5594
sub_4:Test (Best Model) - Loss: 0.5002 - Accuracy: 0.7273 - F1: 0.7179
sub_19:Test (Best Model) - Loss: 1.2359 - Accuracy: 0.4688 - F1: 0.3191
sub_1:Test (Best Model) - Loss: 0.3546 - Accuracy: 0.8438 - F1: 0.8303
sub_11:Test (Best Model) - Loss: 0.3199 - Accuracy: 0.9091 - F1: 0.9060
sub_24:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.6250 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.4973 - Accuracy: 0.7500 - F1: 0.7091
sub_25:Test (Best Model) - Loss: 0.9424 - Accuracy: 0.4375 - F1: 0.3766
sub_23:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.5758 - F1: 0.4225
sub_14:Test (Best Model) - Loss: 0.8604 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3981 - Accuracy: 0.7188 - F1: 0.6632
sub_17:Test (Best Model) - Loss: 0.8864 - Accuracy: 0.5625 - F1: 0.4909
sub_12:Test (Best Model) - Loss: 1.0110 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.8750 - F1: 0.8704
sub_24:Test (Best Model) - Loss: 0.9135 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 0.8939 - Accuracy: 0.5938 - F1: 0.4340
sub_4:Test (Best Model) - Loss: 0.8737 - Accuracy: 0.6364 - F1: 0.5909
sub_27:Test (Best Model) - Loss: 0.8864 - Accuracy: 0.5625 - F1: 0.4909
sub_9:Test (Best Model) - Loss: 0.2987 - Accuracy: 0.8438 - F1: 0.8303
sub_3:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 1.2084 - Accuracy: 0.1818 - F1: 0.1788
sub_17:Test (Best Model) - Loss: 0.5800 - Accuracy: 0.6875 - F1: 0.6364
sub_29:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.6667 - F1: 0.5935
sub_27:Test (Best Model) - Loss: 0.5800 - Accuracy: 0.6875 - F1: 0.6364
sub_1:Test (Best Model) - Loss: 0.3717 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.4869 - Accuracy: 0.8125 - F1: 0.7922
sub_7:Test (Best Model) - Loss: 0.8035 - Accuracy: 0.6875 - F1: 0.6135
sub_4:Test (Best Model) - Loss: 0.4738 - Accuracy: 0.7576 - F1: 0.7273
sub_29:Test (Best Model) - Loss: 0.5191 - Accuracy: 0.7576 - F1: 0.7381
sub_25:Test (Best Model) - Loss: 0.5400 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 0.5331 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.5230 - Accuracy: 0.7500 - F1: 0.7091
sub_15:Test (Best Model) - Loss: 0.5925 - Accuracy: 0.6250 - F1: 0.5844
sub_25:Test (Best Model) - Loss: 0.5462 - Accuracy: 0.5938 - F1: 0.4340
sub_25:Test (Best Model) - Loss: 0.3918 - Accuracy: 0.7812 - F1: 0.7519

=== Summary Results ===

acc: 65.37 ± 6.00
F1: 60.55 ± 7.23
acc-in: 74.65 ± 5.42
F1-in: 70.68 ± 6.16
