lr: 1e-06
sub_14:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.7500 - F1: 0.7500
sub_2:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.3333 - F1: 0.3019
sub_11:Test (Best Model) - Loss: 0.6643 - Accuracy: 0.6970 - F1: 0.6898
sub_1:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6250 - F1: 0.6113
sub_13:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5312 - F1: 0.4910
sub_22:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.7812 - F1: 0.7625
sub_23:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.3636 - F1: 0.3541
sub_16:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4375 - F1: 0.4375
sub_4:Test (Best Model) - Loss: 0.7247 - Accuracy: 0.2727 - F1: 0.2556
sub_5:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.9375 - F1: 0.9373
sub_19:Test (Best Model) - Loss: 0.7662 - Accuracy: 0.3750 - F1: 0.3074
sub_21:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.9375 - F1: 0.9352
sub_10:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5000 - F1: 0.4818
sub_18:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5758 - F1: 0.5558
sub_24:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7812 - F1: 0.7793
sub_3:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5625 - F1: 0.5466
sub_11:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.3333 - F1: 0.2798
sub_25:Test (Best Model) - Loss: 0.7124 - Accuracy: 0.4242 - F1: 0.4046
sub_1:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4375 - F1: 0.4286
sub_20:Test (Best Model) - Loss: 0.7518 - Accuracy: 0.3125 - F1: 0.2381
sub_22:Test (Best Model) - Loss: 0.7347 - Accuracy: 0.2500 - F1: 0.2000
sub_21:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.6250 - F1: 0.5362
sub_27:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5152 - F1: 0.4762
sub_28:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.4980
sub_6:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.6250 - F1: 0.6190
sub_4:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.6061 - F1: 0.5662
sub_7:Test (Best Model) - Loss: 0.6145 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5000 - F1: 0.4818
sub_15:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.3438 - F1: 0.3108
sub_8:Test (Best Model) - Loss: 0.7317 - Accuracy: 0.3750 - F1: 0.2727
sub_2:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.8182 - F1: 0.8180
sub_14:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.4062 - F1: 0.2889
sub_3:Test (Best Model) - Loss: 0.7274 - Accuracy: 0.2812 - F1: 0.2805
sub_11:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.3939 - F1: 0.3182
sub_18:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5758 - F1: 0.5754
sub_1:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.9062 - F1: 0.9039
sub_24:Test (Best Model) - Loss: 0.7247 - Accuracy: 0.2500 - F1: 0.2471
sub_9:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.6250 - F1: 0.6113
sub_13:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.7812 - F1: 0.7519
sub_17:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5152 - F1: 0.4762
sub_23:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6970 - F1: 0.6967
sub_19:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.7812 - F1: 0.7810
sub_16:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.4545 - F1: 0.4500
sub_21:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.4921
sub_12:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 0.7106 - Accuracy: 0.3438 - F1: 0.3379
sub_29:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.8125 - F1: 0.8057
sub_10:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.5938 - F1: 0.4340
sub_2:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.8182 - F1: 0.8036
sub_5:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.3438 - F1: 0.2558
sub_24:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5625 - F1: 0.5556
sub_1:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 0.7317 - Accuracy: 0.3125 - F1: 0.3098
sub_11:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.8182 - F1: 0.8167
sub_25:Test (Best Model) - Loss: 0.7261 - Accuracy: 0.2424 - F1: 0.2311
sub_27:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5758 - F1: 0.5754
sub_13:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.9062 - F1: 0.9015
sub_28:Test (Best Model) - Loss: 0.7340 - Accuracy: 0.2812 - F1: 0.2195
sub_6:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.5625
sub_4:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.8182 - F1: 0.8180
sub_12:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5312 - F1: 0.5077
sub_3:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.5000 - F1: 0.4921
sub_19:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.9062 - F1: 0.9015
sub_15:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.4062 - F1: 0.3764
sub_7:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5938 - F1: 0.5901
sub_29:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5000 - F1: 0.4818
sub_10:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.7273 - F1: 0.7273
sub_16:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7812 - F1: 0.7793
sub_11:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6061 - F1: 0.6002
sub_24:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.7188 - F1: 0.6811
sub_5:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5312 - F1: 0.4684
sub_17:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5758 - F1: 0.5754
sub_13:Test (Best Model) - Loss: 0.7194 - Accuracy: 0.5312 - F1: 0.3469
sub_23:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6061 - F1: 0.5926
sub_4:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.7273 - F1: 0.7232
sub_6:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5938 - F1: 0.5901
sub_9:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6875 - F1: 0.6863
sub_28:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6250 - F1: 0.6250
sub_21:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.7500 - F1: 0.7333
sub_25:Test (Best Model) - Loss: 0.7448 - Accuracy: 0.2727 - F1: 0.2385
sub_2:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.3333 - F1: 0.3177
sub_18:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.7273 - F1: 0.7263
sub_12:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.8438 - F1: 0.8359
sub_14:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.9375 - F1: 0.9365
sub_22:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.8750 - F1: 0.8745
sub_20:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 0.6294 - Accuracy: 0.8438 - F1: 0.8359
sub_19:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.9375 - F1: 0.9373
sub_7:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.6250 - F1: 0.5000
sub_29:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.7500 - F1: 0.7091
sub_16:Test (Best Model) - Loss: 0.7299 - Accuracy: 0.2500 - F1: 0.2227
sub_11:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.7576 - F1: 0.7574
sub_26:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6970 - F1: 0.6967
sub_8:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.8125 - F1: 0.8118
sub_5:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6250 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.6364 - F1: 0.5417
sub_13:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 0.7179 - Accuracy: 0.3636 - F1: 0.3541
sub_17:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.7273 - F1: 0.7232
sub_28:Test (Best Model) - Loss: 0.6232 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.5000 - F1: 0.4818
sub_12:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.7812 - F1: 0.7519
sub_2:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.4545 - F1: 0.4107
sub_22:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4062 - F1: 0.3267
sub_27:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.9697 - F1: 0.9692
sub_14:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4688 - F1: 0.4682
sub_15:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.7500 - F1: 0.7490
sub_3:Test (Best Model) - Loss: 0.7317 - Accuracy: 0.1875 - F1: 0.1746
sub_24:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.7812 - F1: 0.7758
sub_21:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.4062 - F1: 0.3764
sub_29:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5152 - F1: 0.4261
sub_19:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.6875 - F1: 0.6135
sub_16:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.3438 - F1: 0.3379
sub_7:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.4062 - F1: 0.4057
sub_25:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.6667 - F1: 0.6553
sub_8:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.7500 - F1: 0.7091
sub_6:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4062 - F1: 0.3267
sub_13:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.7273 - F1: 0.7273
sub_17:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.9697 - F1: 0.9692
sub_5:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4062 - F1: 0.3267
sub_18:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.8182 - F1: 0.8096
sub_1:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4545 - F1: 0.4540
sub_28:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.5608
sub_14:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.9375 - F1: 0.9352
sub_3:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5758 - F1: 0.5558
sub_15:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6250 - F1: 0.6113
sub_22:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.6970 - F1: 0.6827
sub_10:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.8438 - F1: 0.8303
sub_19:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5938 - F1: 0.4340
sub_26:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.9394 - F1: 0.9380
sub_20:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7500 - F1: 0.7229
sub_16:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5312 - F1: 0.3469
sub_12:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.4545 - F1: 0.4107
sub_21:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5938 - F1: 0.5733
sub_23:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6667 - F1: 0.6330
sub_13:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6562 - F1: 0.6267
sub_2:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.8438 - F1: 0.8359
sub_6:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.8125 - F1: 0.7922
sub_4:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.5152
sub_28:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.6562 - F1: 0.5594
sub_8:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5625 - F1: 0.5556
sub_11:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.9091 - F1: 0.9077
sub_22:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5455 - F1: 0.4457
sub_19:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6875 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.5000 - F1: 0.4667
sub_1:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.7273 - F1: 0.6857
sub_17:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6667 - F1: 0.6330
sub_24:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6875 - F1: 0.6364
sub_5:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6562 - F1: 0.6476
sub_21:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.7500 - F1: 0.7490
sub_26:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.6970 - F1: 0.6967
sub_15:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5312 - F1: 0.5077
sub_20:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4062 - F1: 0.4010
sub_16:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4375 - F1: 0.3766
sub_9:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.3750 - F1: 0.3725
sub_12:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6667 - F1: 0.6654
sub_8:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.7500 - F1: 0.7409
sub_25:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6667 - F1: 0.6330
sub_23:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.2812 - F1: 0.2633
sub_13:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5455 - F1: 0.4762
sub_2:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6875 - F1: 0.6537
sub_27:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.6364 - F1: 0.6360
sub_3:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7576 - F1: 0.7381
sub_6:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5152 - F1: 0.5147
sub_4:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.7576 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6061 - F1: 0.6061
sub_17:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.6364 - F1: 0.6360
sub_14:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.5152
sub_15:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.7812 - F1: 0.7810
sub_10:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.8438 - F1: 0.8359
sub_28:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.7812 - F1: 0.7625
sub_19:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.9688 - F1: 0.9685
sub_24:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5938 - F1: 0.5589
sub_1:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.6061 - F1: 0.5662
sub_18:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.4062 - F1: 0.3552
sub_26:Test (Best Model) - Loss: 0.7377 - Accuracy: 0.2500 - F1: 0.2227
sub_21:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4688 - F1: 0.4421
sub_29:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6875 - F1: 0.6863
sub_9:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.7812 - F1: 0.7810
sub_16:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.7812 - F1: 0.7519
sub_11:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.5455 - F1: 0.4762
sub_12:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.3750 - F1: 0.3651
sub_8:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.4688 - F1: 0.4682
sub_25:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4375 - F1: 0.4000
sub_27:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6667 - F1: 0.6617
sub_4:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.8788 - F1: 0.8787
sub_5:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.6667 - F1: 0.6617
sub_14:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.4667
sub_10:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6562 - F1: 0.6476
sub_24:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.7500 - F1: 0.7333
sub_20:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.7812 - F1: 0.7625
sub_3:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.4848 - F1: 0.4063
sub_18:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.7500 - F1: 0.7091
sub_28:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5312 - F1: 0.5271
sub_1:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.9091 - F1: 0.9077
sub_6:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5152 - F1: 0.4545
sub_13:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6667 - F1: 0.6654
sub_21:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5938 - F1: 0.5733
sub_29:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.8125 - F1: 0.8095
sub_16:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.9375 - F1: 0.9352
sub_11:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5455 - F1: 0.5299
sub_9:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5000 - F1: 0.4818
sub_25:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5312 - F1: 0.4910
sub_23:Test (Best Model) - Loss: 0.6347 - Accuracy: 0.8750 - F1: 0.8667
sub_7:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6875 - F1: 0.6537
sub_2:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.8125 - F1: 0.8125
sub_12:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5455 - F1: 0.5387
sub_8:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6875 - F1: 0.6667
sub_4:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.2727 - F1: 0.2143
sub_22:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.6970 - F1: 0.6591
sub_5:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5455 - F1: 0.5387
sub_19:Test (Best Model) - Loss: 0.6115 - Accuracy: 0.9688 - F1: 0.9680
sub_10:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5312 - F1: 0.5308
sub_26:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.8438 - F1: 0.8303
sub_28:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4688 - F1: 0.3637
sub_24:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4688 - F1: 0.3976
sub_18:Test (Best Model) - Loss: 0.6304 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.4375 - F1: 0.4170
sub_20:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6875 - F1: 0.6825
sub_3:Test (Best Model) - Loss: 0.7117 - Accuracy: 0.4545 - F1: 0.4288
sub_15:Test (Best Model) - Loss: 0.6051 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6970 - F1: 0.6944
sub_29:Test (Best Model) - Loss: 0.6249 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.7551 - Accuracy: 0.2188 - F1: 0.1795
sub_11:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.7576 - F1: 0.7574
sub_16:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5000 - F1: 0.3333
sub_25:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.5938 - F1: 0.5901
sub_9:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.3438 - F1: 0.3379
sub_22:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.0312 - F1: 0.0303
sub_23:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.5000 - F1: 0.4182
sub_5:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5312 - F1: 0.5271
sub_2:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.7500 - F1: 0.7409
sub_7:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.8788 - F1: 0.8731
sub_10:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6970 - F1: 0.6591
sub_14:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4062 - F1: 0.3764
sub_28:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4688 - F1: 0.4231
sub_6:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.7576 - F1: 0.7273
sub_8:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5312 - F1: 0.5271
sub_17:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6667 - F1: 0.6553
sub_1:Test (Best Model) - Loss: 0.6112 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6667 - F1: 0.6553
sub_20:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.7500 - F1: 0.7490
sub_15:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.9062 - F1: 0.9062
sub_4:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.7273 - F1: 0.7179
sub_13:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.8750 - F1: 0.8704
sub_11:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.3636 - F1: 0.3239
sub_29:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7812 - F1: 0.7810
sub_3:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5455 - F1: 0.5299
sub_9:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.9062 - F1: 0.9015
sub_22:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.8750 - F1: 0.8730
sub_5:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 0.7619 - Accuracy: 0.2500 - F1: 0.2000
sub_2:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5152 - F1: 0.5147
sub_10:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5758 - F1: 0.5658
sub_25:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.7339 - Accuracy: 0.1875 - F1: 0.1579
sub_7:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.7812 - F1: 0.7793
sub_16:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.7188 - F1: 0.6632
sub_14:Test (Best Model) - Loss: 0.7311 - Accuracy: 0.0938 - F1: 0.0857
sub_26:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.8438 - F1: 0.8424
sub_6:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6667 - F1: 0.6330
sub_17:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7273 - F1: 0.7232
sub_19:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.4062 - F1: 0.2889
sub_8:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6667 - F1: 0.6654
sub_27:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7273 - F1: 0.7232
sub_15:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.9062 - F1: 0.9062
sub_24:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.6562 - F1: 0.6476
sub_1:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6250 - F1: 0.5000
sub_13:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.8750 - F1: 0.8667
sub_11:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.7273 - F1: 0.6857
sub_22:Test (Best Model) - Loss: 0.7297 - Accuracy: 0.2500 - F1: 0.2471
sub_3:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.7879 - F1: 0.7847
sub_10:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.6364 - F1: 0.5909
sub_29:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.4848 - F1: 0.4772
sub_9:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7812 - F1: 0.7625
sub_21:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.5333
sub_14:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.8125 - F1: 0.7922
sub_25:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.8750 - F1: 0.8704
sub_16:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4375 - F1: 0.4286
sub_4:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5152 - F1: 0.3889
sub_2:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.7273 - F1: 0.7232
sub_26:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.7812 - F1: 0.7793
sub_7:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4062 - F1: 0.3914
sub_19:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.5312 - F1: 0.3469
sub_8:Test (Best Model) - Loss: 0.6325 - Accuracy: 0.9375 - F1: 0.9365
sub_6:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.3939 - F1: 0.3934
sub_17:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.5312 - F1: 0.3469
sub_5:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.8125 - F1: 0.8125
sub_24:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5000 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.8125 - F1: 0.8057
sub_20:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.8485 - F1: 0.8433
sub_13:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.7188 - F1: 0.6632
sub_1:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.3750 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5758 - F1: 0.5722
sub_14:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.7500 - F1: 0.7490
sub_3:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.8788 - F1: 0.8759
sub_16:Test (Best Model) - Loss: 0.7552 - Accuracy: 0.3438 - F1: 0.2558
sub_29:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.7879 - F1: 0.7664
sub_25:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5938 - F1: 0.5733
sub_15:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.2500 - F1: 0.2000
sub_27:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5934
sub_2:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6061 - F1: 0.5926
sub_28:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.9375 - F1: 0.9352
sub_7:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.8125 - F1: 0.7922
sub_10:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.4242 - F1: 0.4221
sub_17:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.3636 - F1: 0.2667
sub_24:Test (Best Model) - Loss: 0.6484 - Accuracy: 0.8438 - F1: 0.8303
sub_5:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.7188 - F1: 0.6632
sub_9:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.2812 - F1: 0.2805
sub_22:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.7273 - F1: 0.6857
sub_4:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.4545 - F1: 0.4107
sub_12:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5000 - F1: 0.4980
sub_1:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.3750 - F1: 0.2727
sub_18:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.2812 - F1: 0.2805
sub_3:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.3333 - F1: 0.3019
sub_16:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6250 - F1: 0.5362
sub_11:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.3333 - F1: 0.3177
sub_25:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5758 - F1: 0.4225
sub_8:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.6875 - F1: 0.6825
sub_2:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.6061 - F1: 0.5196
sub_15:Test (Best Model) - Loss: 0.6210 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.7104 - Accuracy: 0.3438 - F1: 0.3431
sub_17:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6562 - F1: 0.6267
sub_21:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.7188 - F1: 0.7117
sub_10:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.6061 - F1: 0.6046
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.6250 - F1: 0.6250
sub_22:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.9375 - F1: 0.9365
sub_27:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6562 - F1: 0.6267
sub_4:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.6970 - F1: 0.6944
sub_7:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5000 - F1: 0.4921
sub_23:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.8182 - F1: 0.8036
sub_5:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.8750 - F1: 0.8730
sub_12:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.4375 - F1: 0.4000
sub_6:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.7879 - F1: 0.7847
sub_24:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4688 - F1: 0.4555
sub_20:Test (Best Model) - Loss: 0.7249 - Accuracy: 0.3030 - F1: 0.3005
sub_18:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.7188 - F1: 0.6811
sub_29:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4545 - F1: 0.4500
sub_26:Test (Best Model) - Loss: 0.6271 - Accuracy: 0.9062 - F1: 0.9015
sub_19:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.3438 - F1: 0.2874
sub_25:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.3455
sub_9:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.8750 - F1: 0.8667
sub_11:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.3939 - F1: 0.3889
sub_28:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.2500 - F1: 0.2381
sub_8:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.7188 - F1: 0.6946
sub_15:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4688 - F1: 0.4421
sub_14:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6477 - Accuracy: 0.7812 - F1: 0.7810
sub_5:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6250 - F1: 0.6113
sub_21:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.2500 - F1: 0.2471
sub_3:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5455 - F1: 0.4995
sub_29:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.4545 - F1: 0.4107
sub_7:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5312 - F1: 0.5195
sub_20:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6667 - F1: 0.6654
sub_27:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.2500 - F1: 0.2471
sub_23:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6364 - F1: 0.6333
sub_26:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6562 - F1: 0.5883
sub_19:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.9688 - F1: 0.9685
sub_8:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.7188 - F1: 0.7046
sub_6:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.3939 - F1: 0.3889
sub_25:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.7812 - F1: 0.7625
sub_2:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.2727 - F1: 0.2385
sub_18:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.7188 - F1: 0.6946
sub_3:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5758 - F1: 0.5558
sub_7:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6562 - F1: 0.6476
sub_26:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.7812 - F1: 0.7519
sub_15:Test (Best Model) - Loss: 0.7656 - Accuracy: 0.0312 - F1: 0.0303
sub_6:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.4848 - F1: 0.4527
sub_23:Test (Best Model) - Loss: 0.7208 - Accuracy: 0.2424 - F1: 0.2165
sub_25:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5938 - F1: 0.5901
sub_17:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.8750 - F1: 0.8745
sub_9:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6875 - F1: 0.6135
sub_27:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.8750 - F1: 0.8745
sub_26:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7188 - F1: 0.6946
sub_23:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5152 - F1: 0.4762
sub_15:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7812 - F1: 0.7810
sub_9:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.7500 - F1: 0.7500

=== Summary Results ===

acc: 62.25 ± 4.25
F1: 59.69 ± 4.63
acc-in: 62.88 ± 5.04
F1-in: 61.29 ± 5.17
