lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.8750 - F1: 0.8730
sub_1:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.7500 - F1: 0.7409
sub_1:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.6875 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.7188 - F1: 0.6811
sub_1:Test (Best Model) - Loss: 0.6155 - Accuracy: 0.7500 - F1: 0.7229
sub_1:Test (Best Model) - Loss: 0.6189 - Accuracy: 0.7273 - F1: 0.6997
sub_1:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.7273 - F1: 0.6997
sub_1:Test (Best Model) - Loss: 0.5646 - Accuracy: 0.7273 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.6049 - Accuracy: 0.7576 - F1: 0.7556
sub_1:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.8125 - F1: 0.8095
sub_1:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.5389 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.6138 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.8125 - F1: 0.8125
sub_2:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.6364 - F1: 0.6071
sub_2:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.5455 - F1: 0.4762
sub_2:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.6061 - F1: 0.5662
sub_2:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.6875 - F1: 0.6761
sub_2:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.7500 - F1: 0.7500
sub_2:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5312 - F1: 0.5271
sub_2:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.5938 - F1: 0.5733
sub_2:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5000 - F1: 0.5000
sub_2:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5455 - F1: 0.5438
sub_2:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.5758 - F1: 0.5658
sub_2:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5938 - F1: 0.5901
sub_3:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5000 - F1: 0.4980
sub_3:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.4062 - F1: 0.4057
sub_3:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.5625 - F1: 0.5466
sub_3:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.6667 - F1: 0.6553
sub_3:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.5152 - F1: 0.4923
sub_3:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5152 - F1: 0.4261
sub_3:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6364 - F1: 0.5696
sub_3:Test (Best Model) - Loss: 0.7319 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.4242 - F1: 0.4157
sub_3:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.4545 - F1: 0.4540
sub_4:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.6019 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.5754 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.5930 - Accuracy: 0.7273 - F1: 0.6857
sub_4:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.7273 - F1: 0.7102
sub_4:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.6667 - F1: 0.6459
sub_4:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.7879 - F1: 0.7847
sub_4:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.6970 - F1: 0.6591
sub_4:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.6364 - F1: 0.6278
sub_4:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6061 - F1: 0.5815
sub_4:Test (Best Model) - Loss: 0.6440 - Accuracy: 0.6061 - F1: 0.5926
sub_4:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.7576 - F1: 0.7556
sub_4:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.6667 - F1: 0.6654
sub_4:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.6364 - F1: 0.6278
sub_5:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.6250 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.6314 - Accuracy: 0.6250 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.7812 - F1: 0.7810
sub_5:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.4375 - F1: 0.4000
sub_5:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.5312 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.7188 - F1: 0.7185
sub_5:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.5312 - F1: 0.5195
sub_6:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.5312 - F1: 0.5308
sub_6:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.6875 - F1: 0.6761
sub_6:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.7188 - F1: 0.7117
sub_6:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6250 - F1: 0.6000
sub_6:Test (Best Model) - Loss: 0.7272 - Accuracy: 0.5455 - F1: 0.4457
sub_6:Test (Best Model) - Loss: 0.7376 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 0.7296 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 0.7243 - Accuracy: 0.5152 - F1: 0.4923
sub_6:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6970 - F1: 0.6726
sub_6:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.5152 - F1: 0.5147
sub_6:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.6061 - F1: 0.5926
sub_6:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.6364 - F1: 0.6333
sub_6:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.6364 - F1: 0.6192
sub_6:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6061 - F1: 0.6061
sub_7:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.6250 - F1: 0.6113
sub_7:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.7468 - Accuracy: 0.3438 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.4688 - F1: 0.4421
sub_7:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.6250 - F1: 0.6113
sub_7:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.7500 - F1: 0.7490
sub_8:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5625 - F1: 0.5152
sub_8:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5000 - F1: 0.3816
sub_8:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5625 - F1: 0.5466
sub_8:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.5625 - F1: 0.5608
sub_8:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5312 - F1: 0.5271
sub_8:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.3750 - F1: 0.3651
sub_8:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.5135 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.5523 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 0.5502 - Accuracy: 0.8750 - F1: 0.8730
sub_9:Test (Best Model) - Loss: 0.5183 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.7812 - F1: 0.7758
sub_9:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.7812 - F1: 0.7758
sub_9:Test (Best Model) - Loss: 0.6191 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6875 - F1: 0.6364
sub_9:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 0.5356 - Accuracy: 0.6562 - F1: 0.5883
sub_9:Test (Best Model) - Loss: 0.5156 - Accuracy: 0.7812 - F1: 0.7793
sub_9:Test (Best Model) - Loss: 0.5279 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.6875 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 0.4588 - Accuracy: 0.8438 - F1: 0.8359
sub_10:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7188 - F1: 0.6946
sub_10:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.6250 - F1: 0.6250
sub_10:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.7812 - F1: 0.7810
sub_10:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6250 - F1: 0.6113
sub_10:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.6562 - F1: 0.6390
sub_10:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.4375 - F1: 0.3455
sub_10:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5758 - F1: 0.5558
sub_10:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5758 - F1: 0.5658
sub_10:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.6970 - F1: 0.6827
sub_10:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.3636 - F1: 0.3419
sub_11:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.3939 - F1: 0.3797
sub_11:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4242 - F1: 0.4221
sub_11:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.7545 - Accuracy: 0.4242 - F1: 0.3660
sub_11:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5152 - F1: 0.4545
sub_11:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6364 - F1: 0.6333
sub_11:Test (Best Model) - Loss: 0.7261 - Accuracy: 0.4242 - F1: 0.3660
sub_11:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5758 - F1: 0.5558
sub_11:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4545 - F1: 0.3864
sub_11:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6364 - F1: 0.5696
sub_11:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.5758 - F1: 0.5417
sub_12:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.7812 - F1: 0.7703
sub_12:Test (Best Model) - Loss: 0.6028 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.6254 - Accuracy: 0.6875 - F1: 0.6364
sub_12:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6562 - F1: 0.5594
sub_12:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.6364 - F1: 0.5417
sub_12:Test (Best Model) - Loss: 0.5886 - Accuracy: 0.6970 - F1: 0.6591
sub_12:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.8788 - F1: 0.8731
sub_12:Test (Best Model) - Loss: 0.6290 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.6970 - F1: 0.6591
sub_12:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.7500 - F1: 0.7409
sub_12:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.6875 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 0.6052 - Accuracy: 0.6875 - F1: 0.6863
sub_12:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.7500 - F1: 0.7333
sub_13:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.7500 - F1: 0.7333
sub_13:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.5861 - Accuracy: 0.7500 - F1: 0.7229
sub_13:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.5938 - F1: 0.4793
sub_13:Test (Best Model) - Loss: 0.6272 - Accuracy: 0.6667 - F1: 0.6654
sub_13:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5152 - F1: 0.5038
sub_13:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.6667 - F1: 0.6330
sub_13:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6061 - F1: 0.6046
sub_13:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6250 - F1: 0.6113
sub_13:Test (Best Model) - Loss: 0.6248 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.7500 - F1: 0.7409
sub_13:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.6250 - F1: 0.5636
sub_13:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.5625 - F1: 0.5333
sub_14:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4062 - F1: 0.4010
sub_14:Test (Best Model) - Loss: 0.6026 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5312 - F1: 0.5271
sub_14:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.5772 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5312 - F1: 0.5271
sub_14:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5312 - F1: 0.5308
sub_14:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 0.6201 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.5933 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.6135 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 0.5798 - Accuracy: 0.6875 - F1: 0.6875
sub_15:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.7188 - F1: 0.6811
sub_15:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6072 - Accuracy: 0.6875 - F1: 0.6863
sub_15:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.5000 - F1: 0.5000
sub_16:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.4818
sub_16:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6875 - F1: 0.6875
sub_16:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.7188 - F1: 0.7185
sub_16:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.4375 - F1: 0.4000
sub_16:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5312 - F1: 0.5308
sub_17:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5758 - F1: 0.5558
sub_17:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4545 - F1: 0.4288
sub_17:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.6061 - F1: 0.6061
sub_17:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.5455 - F1: 0.4995
sub_17:Test (Best Model) - Loss: 0.7686 - Accuracy: 0.2727 - F1: 0.2556
sub_17:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.5000 - F1: 0.4921
sub_17:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4688 - F1: 0.4421
sub_17:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.5152
sub_17:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5938 - F1: 0.5733
sub_18:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.8485 - F1: 0.8479
sub_18:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.8788 - F1: 0.8731
sub_18:Test (Best Model) - Loss: 0.5760 - Accuracy: 0.8125 - F1: 0.8118
sub_18:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.5312 - F1: 0.5271
sub_18:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.6562 - F1: 0.6476
sub_18:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.7188 - F1: 0.7163
sub_18:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.5616 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7812 - F1: 0.7758
sub_18:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.8125 - F1: 0.8118
sub_19:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.7188 - F1: 0.7117
sub_19:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6562 - F1: 0.6476
sub_19:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.5312 - F1: 0.4684
sub_19:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.6250 - F1: 0.6250
sub_19:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.6875 - F1: 0.6863
sub_19:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.6562 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.6562 - F1: 0.6267
sub_20:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.6372 - Accuracy: 0.6562 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.6562 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5312 - F1: 0.5077
sub_20:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5312 - F1: 0.5308
sub_20:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6970 - F1: 0.6967
sub_20:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.7273 - F1: 0.6997
sub_20:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6061 - F1: 0.6046
sub_20:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6061 - F1: 0.5662
sub_20:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.6364 - F1: 0.6360
sub_21:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5938 - F1: 0.5733
sub_21:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4688 - F1: 0.4640
sub_21:Test (Best Model) - Loss: 0.7204 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.7164 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.4688 - F1: 0.4640
sub_21:Test (Best Model) - Loss: 0.7050 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.7160 - Accuracy: 0.4688 - F1: 0.4682
sub_21:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3750 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 0.7532 - Accuracy: 0.2500 - F1: 0.2381
sub_21:Test (Best Model) - Loss: 0.7358 - Accuracy: 0.3125 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.7153 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.5333
sub_22:Test (Best Model) - Loss: 0.5415 - Accuracy: 0.8750 - F1: 0.8667
sub_22:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.7500 - F1: 0.7460
sub_22:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6250 - F1: 0.5844
sub_22:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5758 - F1: 0.4978
sub_22:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.7576 - F1: 0.7462
sub_22:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 0.6607 - Accuracy: 0.7273 - F1: 0.7263
sub_22:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.6562 - F1: 0.6390
sub_22:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.6875 - F1: 0.6825
sub_22:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6250 - F1: 0.6190
sub_23:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.7273 - F1: 0.7102
sub_23:Test (Best Model) - Loss: 0.5511 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.7576 - F1: 0.7462
sub_23:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.6875 - F1: 0.6825
sub_23:Test (Best Model) - Loss: 0.5880 - Accuracy: 0.7812 - F1: 0.7758
sub_23:Test (Best Model) - Loss: 0.6411 - Accuracy: 0.5938 - F1: 0.5836
sub_23:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.5455 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.5587 - Accuracy: 0.7879 - F1: 0.7806
sub_23:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.7576 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.5953 - Accuracy: 0.8485 - F1: 0.8433
sub_24:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.4062 - F1: 0.4057
sub_24:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.7188 - F1: 0.7185
sub_24:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.5000 - F1: 0.4921
sub_25:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.5152 - F1: 0.5038
sub_25:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.4242 - F1: 0.4221
sub_25:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.3939 - F1: 0.3934
sub_25:Test (Best Model) - Loss: 0.7334 - Accuracy: 0.4242 - F1: 0.3365
sub_25:Test (Best Model) - Loss: 0.7234 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.4062 - F1: 0.4010
sub_25:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.7188 - F1: 0.7117
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5312 - F1: 0.4684
sub_25:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4688 - F1: 0.4682
sub_25:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5000 - F1: 0.4459
sub_25:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.5466
sub_26:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.6970 - F1: 0.6898
sub_26:Test (Best Model) - Loss: 0.5661 - Accuracy: 0.7576 - F1: 0.7381
sub_26:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.8182 - F1: 0.8139
sub_26:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.7576 - F1: 0.7381
sub_26:Test (Best Model) - Loss: 0.5585 - Accuracy: 0.8788 - F1: 0.8731
sub_26:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.6562 - F1: 0.6476
sub_26:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.5938 - F1: 0.5901
sub_26:Test (Best Model) - Loss: 0.6122 - Accuracy: 0.6875 - F1: 0.6875
sub_26:Test (Best Model) - Loss: 0.5639 - Accuracy: 0.8750 - F1: 0.8704
sub_26:Test (Best Model) - Loss: 0.5675 - Accuracy: 0.7812 - F1: 0.7703
sub_26:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.8125 - F1: 0.8000
sub_26:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.7188 - F1: 0.6632
sub_26:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.8438 - F1: 0.8398
sub_27:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4545 - F1: 0.4288
sub_27:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.6061 - F1: 0.6061
sub_27:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.5455 - F1: 0.4995
sub_27:Test (Best Model) - Loss: 0.7686 - Accuracy: 0.2727 - F1: 0.2556
sub_27:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.5000 - F1: 0.4921
sub_27:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4688 - F1: 0.4421
sub_27:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.5152
sub_27:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5938 - F1: 0.5733
sub_28:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6250 - F1: 0.6190
sub_28:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 0.7115 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.7472 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 0.7629 - Accuracy: 0.4375 - F1: 0.4000
sub_28:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.7353 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.6562 - F1: 0.6267
sub_28:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.7213 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5000 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.4921
sub_29:Test (Best Model) - Loss: 0.4778 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.5183 - Accuracy: 0.8125 - F1: 0.8000
sub_29:Test (Best Model) - Loss: 0.4596 - Accuracy: 0.8438 - F1: 0.8359
sub_29:Test (Best Model) - Loss: 0.4842 - Accuracy: 0.8438 - F1: 0.8359
sub_29:Test (Best Model) - Loss: 0.4148 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.5407 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.5448 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.4032 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.4076 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.4218 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.5121 - Accuracy: 0.8485 - F1: 0.8479
sub_29:Test (Best Model) - Loss: 0.5112 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.5552 - Accuracy: 0.7879 - F1: 0.7871
sub_29:Test (Best Model) - Loss: 0.4749 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.4519 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 63.24 ± 9.78
F1: 61.45 ± 10.10
acc-in: 68.80 ± 7.88
F1-in: 66.92 ± 8.29
