lr: 1e-06
sub_8:Test (Best Model) - Loss: 0.3495 - Accuracy: 0.9062 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.2898 - Accuracy: 0.8750 - F1: 0.8750
sub_18:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.5152 - F1: 0.4762
sub_5:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.5312 - F1: 0.5077
sub_15:Test (Best Model) - Loss: 0.4139 - Accuracy: 0.9062 - F1: 0.9039
sub_20:Test (Best Model) - Loss: 0.2736 - Accuracy: 0.9062 - F1: 0.9062
sub_22:Test (Best Model) - Loss: 0.3024 - Accuracy: 0.9688 - F1: 0.9685
sub_6:Test (Best Model) - Loss: 0.4084 - Accuracy: 0.8750 - F1: 0.8745
sub_14:Test (Best Model) - Loss: 0.9232 - Accuracy: 0.4062 - F1: 0.2889
sub_21:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.4700 - Accuracy: 0.7812 - F1: 0.7810
sub_7:Test (Best Model) - Loss: 0.8435 - Accuracy: 0.5312 - F1: 0.4684
sub_12:Test (Best Model) - Loss: 0.4407 - Accuracy: 0.8125 - F1: 0.8095
sub_4:Test (Best Model) - Loss: 0.2287 - Accuracy: 0.9697 - F1: 0.9692
sub_28:Test (Best Model) - Loss: 0.4550 - Accuracy: 0.8438 - F1: 0.8359
sub_3:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.5333
sub_29:Test (Best Model) - Loss: 0.2507 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.7395 - Accuracy: 0.5938 - F1: 0.4793
sub_11:Test (Best Model) - Loss: 0.5935 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.1893 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.4033 - Accuracy: 0.8125 - F1: 0.8118
sub_21:Test (Best Model) - Loss: 1.0639 - Accuracy: 0.2812 - F1: 0.2805
sub_9:Test (Best Model) - Loss: 0.3832 - Accuracy: 0.8438 - F1: 0.8436
sub_1:Test (Best Model) - Loss: 0.2126 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.5816 - Accuracy: 0.6875 - F1: 0.6761
sub_2:Test (Best Model) - Loss: 1.0019 - Accuracy: 0.4242 - F1: 0.3883
sub_26:Test (Best Model) - Loss: 0.2973 - Accuracy: 0.8788 - F1: 0.8787
sub_17:Test (Best Model) - Loss: 0.5420 - Accuracy: 0.6364 - F1: 0.6333
sub_10:Test (Best Model) - Loss: 0.5256 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.1516 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.5420 - Accuracy: 0.6364 - F1: 0.6333
sub_18:Test (Best Model) - Loss: 0.4003 - Accuracy: 0.7576 - F1: 0.7273
sub_16:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.4233 - Accuracy: 0.8438 - F1: 0.8398
sub_6:Test (Best Model) - Loss: 0.7866 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.5221 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.6061 - F1: 0.6046
sub_23:Test (Best Model) - Loss: 1.0575 - Accuracy: 0.2424 - F1: 0.2424
sub_14:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.8691 - Accuracy: 0.4688 - F1: 0.3637
sub_21:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.6250 - F1: 0.5000
sub_16:Test (Best Model) - Loss: 0.8175 - Accuracy: 0.4375 - F1: 0.4375
sub_15:Test (Best Model) - Loss: 0.3877 - Accuracy: 0.8750 - F1: 0.8730
sub_24:Test (Best Model) - Loss: 0.7783 - Accuracy: 0.4062 - F1: 0.4057
sub_5:Test (Best Model) - Loss: 0.7447 - Accuracy: 0.5000 - F1: 0.4980
sub_12:Test (Best Model) - Loss: 0.4216 - Accuracy: 0.8438 - F1: 0.8424
sub_29:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.6875 - F1: 0.6825
sub_8:Test (Best Model) - Loss: 0.9537 - Accuracy: 0.4375 - F1: 0.4286
sub_10:Test (Best Model) - Loss: 0.4010 - Accuracy: 0.8750 - F1: 0.8667
sub_22:Test (Best Model) - Loss: 0.6097 - Accuracy: 0.7188 - F1: 0.6811
sub_20:Test (Best Model) - Loss: 0.4234 - Accuracy: 0.8750 - F1: 0.8704
sub_7:Test (Best Model) - Loss: 0.5185 - Accuracy: 0.8125 - F1: 0.8118
sub_1:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.6875 - F1: 0.6825
sub_11:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.6970 - F1: 0.6827
sub_9:Test (Best Model) - Loss: 1.0437 - Accuracy: 0.3750 - F1: 0.3725
sub_28:Test (Best Model) - Loss: 0.8759 - Accuracy: 0.4062 - F1: 0.3552
sub_3:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6250 - F1: 0.6235
sub_4:Test (Best Model) - Loss: 0.4206 - Accuracy: 0.8182 - F1: 0.8167
sub_2:Test (Best Model) - Loss: 0.6347 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.9091 - F1: 0.9060
sub_12:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.7812 - F1: 0.7519
sub_21:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.6562 - F1: 0.6102
sub_5:Test (Best Model) - Loss: 0.9652 - Accuracy: 0.3750 - F1: 0.3074
sub_8:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.3991 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.6562 - F1: 0.6532
sub_28:Test (Best Model) - Loss: 0.8655 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 0.8608 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.4922 - Accuracy: 0.7273 - F1: 0.7263
sub_20:Test (Best Model) - Loss: 0.5359 - Accuracy: 0.7188 - F1: 0.6811
sub_27:Test (Best Model) - Loss: 0.8726 - Accuracy: 0.4848 - F1: 0.4772
sub_9:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.4688 - F1: 0.4640
sub_17:Test (Best Model) - Loss: 0.8726 - Accuracy: 0.4848 - F1: 0.4772
sub_22:Test (Best Model) - Loss: 0.4715 - Accuracy: 0.7812 - F1: 0.7519
sub_18:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.4242 - F1: 0.2979
sub_6:Test (Best Model) - Loss: 0.5923 - Accuracy: 0.7500 - F1: 0.7333
sub_16:Test (Best Model) - Loss: 0.3260 - Accuracy: 0.8750 - F1: 0.8667
sub_12:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.6875 - F1: 0.6135
sub_13:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.3438 - F1: 0.2558
sub_8:Test (Best Model) - Loss: 1.7832 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 0.5693 - Accuracy: 0.6970 - F1: 0.6944
sub_4:Test (Best Model) - Loss: 0.5162 - Accuracy: 0.7879 - F1: 0.7746
sub_21:Test (Best Model) - Loss: 2.0525 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.5874 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.5000 - F1: 0.4182
sub_22:Test (Best Model) - Loss: 0.3657 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.3470 - Accuracy: 0.8125 - F1: 0.7922
sub_6:Test (Best Model) - Loss: 0.8272 - Accuracy: 0.3438 - F1: 0.3273
sub_24:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.5665 - Accuracy: 0.6970 - F1: 0.6944
sub_12:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.3438 - F1: 0.2558
sub_23:Test (Best Model) - Loss: 0.5041 - Accuracy: 0.8182 - F1: 0.8036
sub_20:Test (Best Model) - Loss: 1.3006 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.4123 - Accuracy: 0.8485 - F1: 0.8462
sub_13:Test (Best Model) - Loss: 0.5386 - Accuracy: 0.7188 - F1: 0.6632
sub_28:Test (Best Model) - Loss: 0.5373 - Accuracy: 0.6250 - F1: 0.5362
sub_10:Test (Best Model) - Loss: 1.0009 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5312 - F1: 0.5308
sub_26:Test (Best Model) - Loss: 0.5201 - Accuracy: 0.6970 - F1: 0.6967
sub_1:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.6562 - F1: 0.5883
sub_7:Test (Best Model) - Loss: 1.4138 - Accuracy: 0.3750 - F1: 0.2727
sub_3:Test (Best Model) - Loss: 0.4554 - Accuracy: 0.8125 - F1: 0.7922
sub_24:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.4062 - F1: 0.2889
sub_16:Test (Best Model) - Loss: 0.5550 - Accuracy: 0.6875 - F1: 0.6135
sub_9:Test (Best Model) - Loss: 0.3036 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 1.4938 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.4062 - F1: 0.2889
sub_29:Test (Best Model) - Loss: 0.5998 - Accuracy: 0.8125 - F1: 0.7922
sub_23:Test (Best Model) - Loss: 0.4366 - Accuracy: 0.8788 - F1: 0.8759
sub_2:Test (Best Model) - Loss: 0.4329 - Accuracy: 0.8182 - F1: 0.8139
sub_27:Test (Best Model) - Loss: 0.4102 - Accuracy: 0.8182 - F1: 0.8180
sub_14:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.8665 - Accuracy: 0.4062 - F1: 0.3914
sub_11:Test (Best Model) - Loss: 0.5046 - Accuracy: 0.7879 - F1: 0.7746
sub_13:Test (Best Model) - Loss: 1.2852 - Accuracy: 0.4062 - F1: 0.3267
sub_15:Test (Best Model) - Loss: 0.3729 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.5455 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.6364 - F1: 0.5696
sub_28:Test (Best Model) - Loss: 1.9813 - Accuracy: 0.3750 - F1: 0.2727
sub_17:Test (Best Model) - Loss: 0.4102 - Accuracy: 0.8182 - F1: 0.8180
sub_1:Test (Best Model) - Loss: 0.4103 - Accuracy: 0.7812 - F1: 0.7519
sub_21:Test (Best Model) - Loss: 0.4070 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 1.2579 - Accuracy: 0.4062 - F1: 0.2889
sub_3:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.9373 - Accuracy: 0.5312 - F1: 0.4684
sub_5:Test (Best Model) - Loss: 0.5876 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 0.5076 - Accuracy: 0.7273 - F1: 0.7179
sub_16:Test (Best Model) - Loss: 0.9522 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.6970 - F1: 0.6591
sub_29:Test (Best Model) - Loss: 1.6959 - Accuracy: 0.4062 - F1: 0.2889
sub_27:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.6970 - F1: 0.6827
sub_23:Test (Best Model) - Loss: 1.6940 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.5581 - Accuracy: 0.7500 - F1: 0.7460
sub_11:Test (Best Model) - Loss: 1.6426 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.9897 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.4261 - Accuracy: 0.7812 - F1: 0.7519
sub_17:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.6970 - F1: 0.6827
sub_28:Test (Best Model) - Loss: 0.3533 - Accuracy: 0.9062 - F1: 0.9039
sub_25:Test (Best Model) - Loss: 1.0053 - Accuracy: 0.3939 - F1: 0.3182
sub_1:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.4062 - F1: 0.2889
sub_24:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.5938 - F1: 0.5733
sub_22:Test (Best Model) - Loss: 0.5290 - Accuracy: 0.6970 - F1: 0.6898
sub_8:Test (Best Model) - Loss: 0.9931 - Accuracy: 0.3125 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 1.0116 - Accuracy: 0.4688 - F1: 0.3637
sub_4:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.4242 - F1: 0.2979
sub_26:Test (Best Model) - Loss: 0.2153 - Accuracy: 0.9697 - F1: 0.9692
sub_5:Test (Best Model) - Loss: 1.9235 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.7188 - F1: 0.6632
sub_27:Test (Best Model) - Loss: 1.6412 - Accuracy: 0.3939 - F1: 0.2826
sub_14:Test (Best Model) - Loss: 0.4638 - Accuracy: 0.7812 - F1: 0.7519
sub_7:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.7812 - F1: 0.7793
sub_10:Test (Best Model) - Loss: 0.5649 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.6061 - F1: 0.5460
sub_19:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.5503 - Accuracy: 0.8182 - F1: 0.8180
sub_17:Test (Best Model) - Loss: 1.6412 - Accuracy: 0.3939 - F1: 0.2826
sub_24:Test (Best Model) - Loss: 1.1667 - Accuracy: 0.4375 - F1: 0.3455
sub_20:Test (Best Model) - Loss: 1.0338 - Accuracy: 0.4375 - F1: 0.3455
sub_21:Test (Best Model) - Loss: 1.1651 - Accuracy: 0.1875 - F1: 0.1875
sub_8:Test (Best Model) - Loss: 0.4899 - Accuracy: 0.7500 - F1: 0.7500
sub_13:Test (Best Model) - Loss: 1.0325 - Accuracy: 0.3939 - F1: 0.2826
sub_2:Test (Best Model) - Loss: 1.6813 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.9999 - Accuracy: 0.5758 - F1: 0.5227
sub_9:Test (Best Model) - Loss: 0.4986 - Accuracy: 0.8125 - F1: 0.8000
sub_14:Test (Best Model) - Loss: 0.8654 - Accuracy: 0.5625 - F1: 0.4167
sub_10:Test (Best Model) - Loss: 1.0515 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.5227 - Accuracy: 0.7576 - F1: 0.7574
sub_15:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.7479 - Accuracy: 0.6364 - F1: 0.6333
sub_29:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.6562 - F1: 0.6476
sub_11:Test (Best Model) - Loss: 0.5785 - Accuracy: 0.6970 - F1: 0.6967
sub_23:Test (Best Model) - Loss: 0.7806 - Accuracy: 0.5000 - F1: 0.4818
sub_13:Test (Best Model) - Loss: 0.9571 - Accuracy: 0.2121 - F1: 0.2114
sub_8:Test (Best Model) - Loss: 1.6344 - Accuracy: 0.3750 - F1: 0.2727
sub_22:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.5758 - F1: 0.4225
sub_4:Test (Best Model) - Loss: 0.3184 - Accuracy: 0.9697 - F1: 0.9696
sub_28:Test (Best Model) - Loss: 0.7961 - Accuracy: 0.5000 - F1: 0.4182
sub_2:Test (Best Model) - Loss: 0.7406 - Accuracy: 0.4688 - F1: 0.4555
sub_16:Test (Best Model) - Loss: 0.5529 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 0.8334 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.5258 - Accuracy: 0.7500 - F1: 0.7490
sub_20:Test (Best Model) - Loss: 0.5527 - Accuracy: 0.7188 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.3030 - F1: 0.3005
sub_19:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.5938 - F1: 0.5733
sub_6:Test (Best Model) - Loss: 1.0379 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7539 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.4503 - Accuracy: 0.8438 - F1: 0.8359
sub_1:Test (Best Model) - Loss: 0.9115 - Accuracy: 0.4545 - F1: 0.3543
sub_16:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5000 - F1: 0.4459
sub_8:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.6562 - F1: 0.6476
sub_4:Test (Best Model) - Loss: 0.9106 - Accuracy: 0.5152 - F1: 0.3400
sub_24:Test (Best Model) - Loss: 0.8855 - Accuracy: 0.4062 - F1: 0.2889
sub_7:Test (Best Model) - Loss: 0.4488 - Accuracy: 0.7812 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.9556 - Accuracy: 0.4242 - F1: 0.2979
sub_9:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.6562 - F1: 0.5594
sub_25:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.6875 - F1: 0.6135
sub_27:Test (Best Model) - Loss: 0.9308 - Accuracy: 0.4545 - F1: 0.3543
sub_14:Test (Best Model) - Loss: 0.5332 - Accuracy: 0.7812 - F1: 0.7758
sub_17:Test (Best Model) - Loss: 0.9308 - Accuracy: 0.4545 - F1: 0.3543
sub_26:Test (Best Model) - Loss: 0.8276 - Accuracy: 0.5938 - F1: 0.5733
sub_22:Test (Best Model) - Loss: 0.7198 - Accuracy: 0.6061 - F1: 0.5926
sub_6:Test (Best Model) - Loss: 1.0402 - Accuracy: 0.3636 - F1: 0.3239
sub_10:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5938 - F1: 0.5135
sub_12:Test (Best Model) - Loss: 1.0233 - Accuracy: 0.4848 - F1: 0.3718
sub_21:Test (Best Model) - Loss: 1.0942 - Accuracy: 0.4062 - F1: 0.3267
sub_16:Test (Best Model) - Loss: 0.9568 - Accuracy: 0.5000 - F1: 0.4182
sub_24:Test (Best Model) - Loss: 0.8427 - Accuracy: 0.4062 - F1: 0.3764
sub_20:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.5625 - F1: 0.5152
sub_8:Test (Best Model) - Loss: 0.5190 - Accuracy: 0.6875 - F1: 0.6761
sub_28:Test (Best Model) - Loss: 0.4291 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 0.8582 - Accuracy: 0.5312 - F1: 0.3992
sub_7:Test (Best Model) - Loss: 0.7823 - Accuracy: 0.4375 - F1: 0.4286
sub_14:Test (Best Model) - Loss: 0.7980 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.4095 - Accuracy: 0.8125 - F1: 0.8000
sub_23:Test (Best Model) - Loss: 0.9629 - Accuracy: 0.3125 - F1: 0.2874
sub_5:Test (Best Model) - Loss: 0.8278 - Accuracy: 0.4688 - F1: 0.4555
sub_27:Test (Best Model) - Loss: 0.9247 - Accuracy: 0.4848 - F1: 0.3718
sub_15:Test (Best Model) - Loss: 1.0274 - Accuracy: 0.2500 - F1: 0.2000
sub_22:Test (Best Model) - Loss: 1.8191 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.4259 - Accuracy: 0.8750 - F1: 0.8745
sub_29:Test (Best Model) - Loss: 0.7343 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.8241 - Accuracy: 0.5758 - F1: 0.4225
sub_17:Test (Best Model) - Loss: 0.9247 - Accuracy: 0.4848 - F1: 0.3718
sub_20:Test (Best Model) - Loss: 1.2379 - Accuracy: 0.2500 - F1: 0.2000
sub_21:Test (Best Model) - Loss: 0.5436 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 0.7700 - Accuracy: 0.4848 - F1: 0.3718
sub_9:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.5312 - F1: 0.5308
sub_14:Test (Best Model) - Loss: 0.7384 - Accuracy: 0.4688 - F1: 0.4555
sub_7:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 1.0572 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.4214 - Accuracy: 0.8182 - F1: 0.8180
sub_28:Test (Best Model) - Loss: 0.4046 - Accuracy: 0.8438 - F1: 0.8436
sub_18:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.5625 - F1: 0.5152
sub_19:Test (Best Model) - Loss: 0.8088 - Accuracy: 0.5625 - F1: 0.5333
sub_26:Test (Best Model) - Loss: 0.5884 - Accuracy: 0.6250 - F1: 0.6000
sub_27:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6667 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.5196 - Accuracy: 0.6667 - F1: 0.6459
sub_3:Test (Best Model) - Loss: 0.9128 - Accuracy: 0.4848 - F1: 0.4063
sub_2:Test (Best Model) - Loss: 0.9593 - Accuracy: 0.3750 - F1: 0.2727
sub_4:Test (Best Model) - Loss: 0.3905 - Accuracy: 0.7879 - F1: 0.7664
sub_20:Test (Best Model) - Loss: 1.2893 - Accuracy: 0.3636 - F1: 0.2667
sub_11:Test (Best Model) - Loss: 1.0057 - Accuracy: 0.3636 - F1: 0.3239
sub_17:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6667 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 1.0622 - Accuracy: 0.4688 - F1: 0.3637
sub_10:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4375 - F1: 0.3766
sub_29:Test (Best Model) - Loss: 0.2903 - Accuracy: 0.8750 - F1: 0.8667
sub_25:Test (Best Model) - Loss: 0.4301 - Accuracy: 0.7188 - F1: 0.7163
sub_7:Test (Best Model) - Loss: 0.9647 - Accuracy: 0.5312 - F1: 0.5077
sub_18:Test (Best Model) - Loss: 1.1073 - Accuracy: 0.2812 - F1: 0.2633
sub_23:Test (Best Model) - Loss: 0.2145 - Accuracy: 0.9688 - F1: 0.9685
sub_8:Test (Best Model) - Loss: 0.5979 - Accuracy: 0.6562 - F1: 0.6559
sub_21:Test (Best Model) - Loss: 0.7739 - Accuracy: 0.6562 - F1: 0.6390
sub_22:Test (Best Model) - Loss: 0.9240 - Accuracy: 0.6061 - F1: 0.5815
sub_4:Test (Best Model) - Loss: 1.3341 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.4244 - Accuracy: 0.7812 - F1: 0.7810
sub_15:Test (Best Model) - Loss: 0.3690 - Accuracy: 0.8438 - F1: 0.8436
sub_27:Test (Best Model) - Loss: 0.9558 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.8750 - F1: 0.8667
sub_3:Test (Best Model) - Loss: 0.5118 - Accuracy: 0.7576 - F1: 0.7462
sub_13:Test (Best Model) - Loss: 1.0571 - Accuracy: 0.3939 - F1: 0.2826
sub_28:Test (Best Model) - Loss: 0.4747 - Accuracy: 0.8438 - F1: 0.8303
sub_2:Test (Best Model) - Loss: 0.8029 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.9558 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.7130 - Accuracy: 0.5312 - F1: 0.4910
sub_10:Test (Best Model) - Loss: 0.7404 - Accuracy: 0.6364 - F1: 0.6278
sub_1:Test (Best Model) - Loss: 1.0143 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.5758 - F1: 0.5658
sub_4:Test (Best Model) - Loss: 1.2907 - Accuracy: 0.2727 - F1: 0.2385
sub_11:Test (Best Model) - Loss: 1.4534 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7576 - F1: 0.7381
sub_9:Test (Best Model) - Loss: 0.4920 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5000 - F1: 0.4182
sub_10:Test (Best Model) - Loss: 1.0054 - Accuracy: 0.3939 - F1: 0.3182
sub_16:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 0.8881 - Accuracy: 0.5312 - F1: 0.5077
sub_21:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.3024 - Accuracy: 0.8750 - F1: 0.8750
sub_27:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6364 - F1: 0.6071
sub_18:Test (Best Model) - Loss: 0.6153 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 1.5679 - Accuracy: 0.3333 - F1: 0.2500
sub_2:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.6250 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 1.0081 - Accuracy: 0.5000 - F1: 0.4182
sub_14:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5938 - F1: 0.5589
sub_19:Test (Best Model) - Loss: 0.3402 - Accuracy: 0.8438 - F1: 0.8303
sub_17:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6364 - F1: 0.6071
sub_13:Test (Best Model) - Loss: 1.0904 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.3811 - Accuracy: 0.8125 - F1: 0.8118
sub_24:Test (Best Model) - Loss: 0.4425 - Accuracy: 0.7812 - F1: 0.7793
sub_10:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.6970 - F1: 0.6413
sub_28:Test (Best Model) - Loss: 1.2940 - Accuracy: 0.1875 - F1: 0.1579
sub_8:Test (Best Model) - Loss: 0.8112 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.5161 - Accuracy: 0.6875 - F1: 0.6825
sub_3:Test (Best Model) - Loss: 1.0442 - Accuracy: 0.4848 - F1: 0.3718
sub_22:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.6562 - F1: 0.6532
sub_23:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.5000 - F1: 0.4182
sub_29:Test (Best Model) - Loss: 0.7913 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.7752 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.5938 - F1: 0.5836
sub_20:Test (Best Model) - Loss: 0.7311 - Accuracy: 0.6364 - F1: 0.5696
sub_4:Test (Best Model) - Loss: 0.4609 - Accuracy: 0.7576 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.8173 - Accuracy: 0.5312 - F1: 0.4684
sub_6:Test (Best Model) - Loss: 0.2688 - Accuracy: 0.9697 - F1: 0.9692
sub_16:Test (Best Model) - Loss: 1.0163 - Accuracy: 0.3125 - F1: 0.3098
sub_15:Test (Best Model) - Loss: 1.1531 - Accuracy: 0.3438 - F1: 0.2558
sub_19:Test (Best Model) - Loss: 0.4256 - Accuracy: 0.8125 - F1: 0.8125
sub_5:Test (Best Model) - Loss: 0.7684 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.6562 - F1: 0.5594
sub_10:Test (Best Model) - Loss: 0.7624 - Accuracy: 0.5758 - F1: 0.4653
sub_1:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.1474 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.7188 - F1: 0.6811
sub_18:Test (Best Model) - Loss: 0.5682 - Accuracy: 0.6875 - F1: 0.6875
sub_2:Test (Best Model) - Loss: 0.3857 - Accuracy: 0.9697 - F1: 0.9696
sub_22:Test (Best Model) - Loss: 0.8166 - Accuracy: 0.6562 - F1: 0.5594
sub_20:Test (Best Model) - Loss: 0.7655 - Accuracy: 0.6061 - F1: 0.5196
sub_13:Test (Best Model) - Loss: 0.7768 - Accuracy: 0.5625 - F1: 0.5333
sub_14:Test (Best Model) - Loss: 0.4724 - Accuracy: 0.7500 - F1: 0.7091
sub_6:Test (Best Model) - Loss: 0.4720 - Accuracy: 0.6970 - F1: 0.6967
sub_12:Test (Best Model) - Loss: 0.4605 - Accuracy: 0.7812 - F1: 0.7519
sub_24:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.5625 - F1: 0.5333
sub_27:Test (Best Model) - Loss: 0.7545 - Accuracy: 0.6250 - F1: 0.6235
sub_21:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.6562 - F1: 0.6559
sub_28:Test (Best Model) - Loss: 0.9901 - Accuracy: 0.3438 - F1: 0.3431
sub_11:Test (Best Model) - Loss: 0.5071 - Accuracy: 0.6667 - F1: 0.6553
sub_3:Test (Best Model) - Loss: 0.3737 - Accuracy: 0.8485 - F1: 0.8479
sub_16:Test (Best Model) - Loss: 1.0110 - Accuracy: 0.5312 - F1: 0.3469
sub_17:Test (Best Model) - Loss: 0.7545 - Accuracy: 0.6250 - F1: 0.6235
sub_22:Test (Best Model) - Loss: 0.4860 - Accuracy: 0.7812 - F1: 0.7519
sub_2:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.5758 - F1: 0.5754
sub_1:Test (Best Model) - Loss: 0.6165 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 1.0860 - Accuracy: 0.4062 - F1: 0.3764
sub_26:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.2188 - F1: 0.1795
sub_4:Test (Best Model) - Loss: 0.5760 - Accuracy: 0.7576 - F1: 0.7574
sub_24:Test (Best Model) - Loss: 0.5280 - Accuracy: 0.6562 - F1: 0.5594
sub_28:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6562 - F1: 0.5594
sub_10:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.5455 - F1: 0.4058
sub_20:Test (Best Model) - Loss: 0.7919 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.9855 - Accuracy: 0.5000 - F1: 0.4459
sub_6:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.6364 - F1: 0.5696
sub_19:Test (Best Model) - Loss: 0.5888 - Accuracy: 0.7188 - F1: 0.7185
sub_21:Test (Best Model) - Loss: 1.3992 - Accuracy: 0.2500 - F1: 0.2381
sub_22:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.5625 - F1: 0.4167
sub_18:Test (Best Model) - Loss: 0.2906 - Accuracy: 0.9375 - F1: 0.9365
sub_5:Test (Best Model) - Loss: 1.0366 - Accuracy: 0.4688 - F1: 0.3637
sub_3:Test (Best Model) - Loss: 0.7430 - Accuracy: 0.6061 - F1: 0.5926
sub_15:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.3750 - F1: 0.2727
sub_14:Test (Best Model) - Loss: 1.0033 - Accuracy: 0.5938 - F1: 0.4340
sub_25:Test (Best Model) - Loss: 0.7902 - Accuracy: 0.5000 - F1: 0.4921
sub_29:Test (Best Model) - Loss: 0.3670 - Accuracy: 0.8485 - F1: 0.8485
sub_12:Test (Best Model) - Loss: 0.9216 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.5925 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 1.1489 - Accuracy: 0.5312 - F1: 0.3469
sub_28:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.6250 - F1: 0.5636
sub_1:Test (Best Model) - Loss: 0.2740 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.2496 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.5938 - F1: 0.4340
sub_7:Test (Best Model) - Loss: 0.5184 - Accuracy: 0.7188 - F1: 0.7163
sub_22:Test (Best Model) - Loss: 0.7737 - Accuracy: 0.6250 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.6364 - F1: 0.5417
sub_14:Test (Best Model) - Loss: 0.9514 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.5875 - Accuracy: 0.7273 - F1: 0.6997
sub_26:Test (Best Model) - Loss: 0.3002 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.7188 - F1: 0.6632
sub_24:Test (Best Model) - Loss: 0.9643 - Accuracy: 0.5938 - F1: 0.4340
sub_27:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.7534 - Accuracy: 0.6250 - F1: 0.5362
sub_12:Test (Best Model) - Loss: 0.9538 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 1.0412 - Accuracy: 0.3636 - F1: 0.3239
sub_17:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.5540 - Accuracy: 0.6667 - F1: 0.6617
sub_21:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6250 - F1: 0.5844
sub_4:Test (Best Model) - Loss: 1.0734 - Accuracy: 0.4848 - F1: 0.3718
sub_13:Test (Best Model) - Loss: 1.0173 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.9385 - Accuracy: 0.5758 - F1: 0.4225
sub_15:Test (Best Model) - Loss: 0.7780 - Accuracy: 0.6250 - F1: 0.5636
sub_11:Test (Best Model) - Loss: 0.3625 - Accuracy: 0.8485 - F1: 0.8485
sub_26:Test (Best Model) - Loss: 0.4063 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.6875 - F1: 0.6825
sub_17:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.6875 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.7188 - F1: 0.6632
sub_3:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6364 - F1: 0.5417
sub_21:Test (Best Model) - Loss: 0.8186 - Accuracy: 0.5000 - F1: 0.3816
sub_2:Test (Best Model) - Loss: 1.0570 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.5028 - Accuracy: 0.7576 - F1: 0.7273
sub_29:Test (Best Model) - Loss: 0.5011 - Accuracy: 0.7576 - F1: 0.7556
sub_26:Test (Best Model) - Loss: 0.8761 - Accuracy: 0.5312 - F1: 0.3469
sub_7:Test (Best Model) - Loss: 0.5422 - Accuracy: 0.7500 - F1: 0.7333
sub_5:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5312 - F1: 0.5308
sub_13:Test (Best Model) - Loss: 0.5743 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 0.5483 - Accuracy: 0.6562 - F1: 0.6390
sub_25:Test (Best Model) - Loss: 0.4160 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.7240 - Accuracy: 0.6562 - F1: 0.5883
sub_11:Test (Best Model) - Loss: 0.4747 - Accuracy: 0.8182 - F1: 0.8139
sub_23:Test (Best Model) - Loss: 0.9906 - Accuracy: 0.3939 - F1: 0.3182
sub_7:Test (Best Model) - Loss: 0.3556 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.6562 - F1: 0.5594
sub_17:Test (Best Model) - Loss: 0.9822 - Accuracy: 0.4062 - F1: 0.3267
sub_1:Test (Best Model) - Loss: 0.4833 - Accuracy: 0.7188 - F1: 0.6632
sub_27:Test (Best Model) - Loss: 0.9822 - Accuracy: 0.4062 - F1: 0.3267
sub_3:Test (Best Model) - Loss: 0.6168 - Accuracy: 0.6667 - F1: 0.6159
sub_9:Test (Best Model) - Loss: 0.4619 - Accuracy: 0.7188 - F1: 0.6632
sub_7:Test (Best Model) - Loss: 0.7500 - Accuracy: 0.6250 - F1: 0.5636
sub_11:Test (Best Model) - Loss: 1.2560 - Accuracy: 0.3333 - F1: 0.2798
sub_29:Test (Best Model) - Loss: 0.7869 - Accuracy: 0.3939 - F1: 0.3452
sub_5:Test (Best Model) - Loss: 0.5059 - Accuracy: 0.7812 - F1: 0.7519
sub_25:Test (Best Model) - Loss: 0.5385 - Accuracy: 0.7188 - F1: 0.6632
sub_23:Test (Best Model) - Loss: 0.5749 - Accuracy: 0.7879 - F1: 0.7806
sub_27:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.5938 - F1: 0.5135
sub_17:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.5938 - F1: 0.5135
sub_15:Test (Best Model) - Loss: 0.7296 - Accuracy: 0.5938 - F1: 0.5393
sub_3:Test (Best Model) - Loss: 1.0689 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.9069 - Accuracy: 0.3438 - F1: 0.3108
sub_5:Test (Best Model) - Loss: 0.7949 - Accuracy: 0.5000 - F1: 0.4182
sub_29:Test (Best Model) - Loss: 0.6086 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.4778 - Accuracy: 0.7879 - F1: 0.7806
sub_3:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6061 - F1: 0.4850
sub_25:Test (Best Model) - Loss: 0.7983 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.6970 - F1: 0.6726
sub_11:Test (Best Model) - Loss: 1.1053 - Accuracy: 0.2727 - F1: 0.2667
sub_25:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6250 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 0.8799 - Accuracy: 0.4688 - F1: 0.3191
sub_29:Test (Best Model) - Loss: 0.4699 - Accuracy: 0.8182 - F1: 0.8096
sub_15:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 0.4323 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.7452 - Accuracy: 0.6061 - F1: 0.4850
sub_19:Test (Best Model) - Loss: 1.2608 - Accuracy: 0.5312 - F1: 0.3469
sub_19:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.7812 - F1: 0.7625

=== Summary Results ===

acc: 61.70 ± 4.21
F1: 56.64 ± 5.11
acc-in: 70.10 ± 3.38
F1-in: 65.65 ± 3.71
