lr: 0.0001
sub_6:Test (Best Model) - Loss: 0.5734 - Accuracy: 0.8750 - F1: 0.8745
sub_11:Test (Best Model) - Loss: 0.5646 - Accuracy: 0.9091 - F1: 0.9077
sub_23:Test (Best Model) - Loss: 0.5014 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.5300 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.5583 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.4917 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.5121 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.5057 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.5210 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.4952 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.4888 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6215 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.9375 - F1: 0.9365
sub_8:Test (Best Model) - Loss: 0.5283 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.5789 - Accuracy: 0.8485 - F1: 0.8433
sub_9:Test (Best Model) - Loss: 0.5241 - Accuracy: 0.9375 - F1: 0.9373
sub_10:Test (Best Model) - Loss: 0.5275 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.4988 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.5162 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.5154 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.5421 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.5982 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.5341 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.4985 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.4855 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4917 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.5368 - Accuracy: 0.9688 - F1: 0.9680
sub_25:Test (Best Model) - Loss: 0.5075 - Accuracy: 0.9394 - F1: 0.9380
sub_16:Test (Best Model) - Loss: 0.5044 - Accuracy: 0.9375 - F1: 0.9352
sub_11:Test (Best Model) - Loss: 0.5312 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.5065 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.4812 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.4661 - Accuracy: 0.9697 - F1: 0.9692
sub_18:Test (Best Model) - Loss: 0.4882 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.5247 - Accuracy: 0.9375 - F1: 0.9365
sub_9:Test (Best Model) - Loss: 0.5143 - Accuracy: 0.9375 - F1: 0.9373
sub_24:Test (Best Model) - Loss: 0.5117 - Accuracy: 0.9688 - F1: 0.9680
sub_21:Test (Best Model) - Loss: 0.5022 - Accuracy: 0.8750 - F1: 0.8667
sub_10:Test (Best Model) - Loss: 0.5103 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.8750 - F1: 0.8750
sub_25:Test (Best Model) - Loss: 0.5255 - Accuracy: 0.9697 - F1: 0.9692
sub_4:Test (Best Model) - Loss: 0.4897 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.5051 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.5658 - Accuracy: 0.9375 - F1: 0.9373
sub_13:Test (Best Model) - Loss: 0.4725 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.4510 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.5443 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.9688 - F1: 0.9685
sub_2:Test (Best Model) - Loss: 0.5805 - Accuracy: 0.8485 - F1: 0.8462
sub_23:Test (Best Model) - Loss: 0.4730 - Accuracy: 0.9697 - F1: 0.9692
sub_11:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.8485 - F1: 0.8462
sub_20:Test (Best Model) - Loss: 0.5090 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.4625 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.5553 - Accuracy: 0.9375 - F1: 0.9352
sub_6:Test (Best Model) - Loss: 0.5641 - Accuracy: 0.8438 - F1: 0.8436
sub_27:Test (Best Model) - Loss: 0.4661 - Accuracy: 0.9697 - F1: 0.9692
sub_15:Test (Best Model) - Loss: 0.4778 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.4631 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4311 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.9375 - F1: 0.9365
sub_16:Test (Best Model) - Loss: 0.4968 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.3994 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.5373 - Accuracy: 0.9062 - F1: 0.9015
sub_17:Test (Best Model) - Loss: 0.4629 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.4611 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.5170 - Accuracy: 0.9688 - F1: 0.9685
sub_25:Test (Best Model) - Loss: 0.5478 - Accuracy: 0.9394 - F1: 0.9380
sub_9:Test (Best Model) - Loss: 0.4531 - Accuracy: 0.9688 - F1: 0.9685
sub_13:Test (Best Model) - Loss: 0.5032 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.5209 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.4246 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.4994 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.4625 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.4919 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.4329 - Accuracy: 0.9697 - F1: 0.9692
sub_20:Test (Best Model) - Loss: 0.5280 - Accuracy: 0.9062 - F1: 0.9015
sub_23:Test (Best Model) - Loss: 0.4917 - Accuracy: 0.9091 - F1: 0.9060
sub_7:Test (Best Model) - Loss: 0.4527 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.4920 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6019 - Accuracy: 0.7500 - F1: 0.7490
sub_2:Test (Best Model) - Loss: 0.5172 - Accuracy: 0.8788 - F1: 0.8759
sub_8:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7500 - F1: 0.7091
sub_24:Test (Best Model) - Loss: 0.4901 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.5439 - Accuracy: 0.9375 - F1: 0.9352
sub_12:Test (Best Model) - Loss: 0.4769 - Accuracy: 0.9688 - F1: 0.9680
sub_21:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.8750 - F1: 0.8667
sub_3:Test (Best Model) - Loss: 0.4725 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.5133 - Accuracy: 0.9697 - F1: 0.9696
sub_11:Test (Best Model) - Loss: 0.5657 - Accuracy: 0.7879 - F1: 0.7664
sub_25:Test (Best Model) - Loss: 0.5236 - Accuracy: 0.9394 - F1: 0.9380
sub_27:Test (Best Model) - Loss: 0.4629 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4132 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4458 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.5083 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.4736 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.4691 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.4939 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.8125 - F1: 0.8000
sub_17:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.9697 - F1: 0.9692
sub_13:Test (Best Model) - Loss: 0.4545 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5256 - Accuracy: 0.8750 - F1: 0.8704
sub_16:Test (Best Model) - Loss: 0.4553 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.9062 - F1: 0.9054
sub_18:Test (Best Model) - Loss: 0.4484 - Accuracy: 0.9697 - F1: 0.9696
sub_15:Test (Best Model) - Loss: 0.5025 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.5017 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.5633 - Accuracy: 0.8485 - F1: 0.8433
sub_4:Test (Best Model) - Loss: 0.4156 - Accuracy: 0.9697 - F1: 0.9692
sub_7:Test (Best Model) - Loss: 0.4472 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.5714 - Accuracy: 0.9688 - F1: 0.9680
sub_11:Test (Best Model) - Loss: 0.5563 - Accuracy: 0.9697 - F1: 0.9692
sub_23:Test (Best Model) - Loss: 0.4502 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.4499 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4782 - Accuracy: 0.9688 - F1: 0.9685
sub_3:Test (Best Model) - Loss: 0.4926 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.5271 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.5245 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.5123 - Accuracy: 0.9091 - F1: 0.9060
sub_27:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.9697 - F1: 0.9692
sub_12:Test (Best Model) - Loss: 0.4870 - Accuracy: 0.8750 - F1: 0.8667
sub_19:Test (Best Model) - Loss: 0.4965 - Accuracy: 0.9375 - F1: 0.9373
sub_20:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.9062 - F1: 0.9015
sub_6:Test (Best Model) - Loss: 0.5037 - Accuracy: 0.9394 - F1: 0.9380
sub_16:Test (Best Model) - Loss: 0.5237 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.9062 - F1: 0.9015
sub_5:Test (Best Model) - Loss: 0.4792 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4874 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.4744 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.4948 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.5462 - Accuracy: 0.9697 - F1: 0.9692
sub_28:Test (Best Model) - Loss: 0.4817 - Accuracy: 0.9375 - F1: 0.9352
sub_24:Test (Best Model) - Loss: 0.4571 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.4432 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.5008 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.5161 - Accuracy: 0.9394 - F1: 0.9393
sub_13:Test (Best Model) - Loss: 0.4693 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5685 - Accuracy: 0.8125 - F1: 0.8118
sub_10:Test (Best Model) - Loss: 0.6197 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.5508 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.4536 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.5109 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.8750 - F1: 0.8667
sub_27:Test (Best Model) - Loss: 0.4948 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4774 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.4972 - Accuracy: 0.9062 - F1: 0.9062
sub_1:Test (Best Model) - Loss: 0.4673 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.4602 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5659 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.5143 - Accuracy: 0.9091 - F1: 0.9060
sub_25:Test (Best Model) - Loss: 0.4558 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.4532 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.4843 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.4472 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.4722 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.5037 - Accuracy: 0.9688 - F1: 0.9685
sub_20:Test (Best Model) - Loss: 0.4746 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.5103 - Accuracy: 0.9091 - F1: 0.9060
sub_16:Test (Best Model) - Loss: 0.5089 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.5052 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.4181 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.4148 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.4581 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.8750 - F1: 0.8750
sub_13:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.9697 - F1: 0.9692
sub_14:Test (Best Model) - Loss: 0.4870 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.7188 - F1: 0.7117
sub_27:Test (Best Model) - Loss: 0.5109 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.9375 - F1: 0.9365
sub_11:Test (Best Model) - Loss: 0.4858 - Accuracy: 0.9394 - F1: 0.9389
sub_7:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.5246 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5137 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.4804 - Accuracy: 0.9697 - F1: 0.9696
sub_26:Test (Best Model) - Loss: 0.5328 - Accuracy: 0.9062 - F1: 0.9062
sub_1:Test (Best Model) - Loss: 0.4880 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.4942 - Accuracy: 0.9688 - F1: 0.9685
sub_6:Test (Best Model) - Loss: 0.5176 - Accuracy: 0.9394 - F1: 0.9380
sub_22:Test (Best Model) - Loss: 0.5258 - Accuracy: 0.8182 - F1: 0.8167
sub_29:Test (Best Model) - Loss: 0.5151 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.4819 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.4931 - Accuracy: 0.9091 - F1: 0.9060
sub_28:Test (Best Model) - Loss: 0.4951 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.4661 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.4895 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.9688 - F1: 0.9685
sub_20:Test (Best Model) - Loss: 0.4883 - Accuracy: 0.9688 - F1: 0.9680
sub_16:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.9688 - F1: 0.9685
sub_10:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.9375 - F1: 0.9352
sub_23:Test (Best Model) - Loss: 0.5604 - Accuracy: 0.8750 - F1: 0.8750
sub_4:Test (Best Model) - Loss: 0.4737 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4804 - Accuracy: 0.9697 - F1: 0.9696
sub_5:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.9688 - F1: 0.9685
sub_26:Test (Best Model) - Loss: 0.5228 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.9375 - F1: 0.9365
sub_17:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.9697 - F1: 0.9696
sub_21:Test (Best Model) - Loss: 0.5128 - Accuracy: 0.9375 - F1: 0.9373
sub_13:Test (Best Model) - Loss: 0.4726 - Accuracy: 0.9697 - F1: 0.9692
sub_11:Test (Best Model) - Loss: 0.5309 - Accuracy: 0.9091 - F1: 0.9091
sub_19:Test (Best Model) - Loss: 0.4427 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.4672 - Accuracy: 0.9375 - F1: 0.9373
sub_9:Test (Best Model) - Loss: 0.4986 - Accuracy: 0.8750 - F1: 0.8730
sub_25:Test (Best Model) - Loss: 0.5056 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.5084 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.5132 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5003 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.5736 - Accuracy: 0.7576 - F1: 0.7574
sub_12:Test (Best Model) - Loss: 0.5148 - Accuracy: 0.9091 - F1: 0.9060
sub_6:Test (Best Model) - Loss: 0.5296 - Accuracy: 0.9091 - F1: 0.9060
sub_8:Test (Best Model) - Loss: 0.5153 - Accuracy: 0.9688 - F1: 0.9680
sub_15:Test (Best Model) - Loss: 0.4831 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.4949 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.9697 - F1: 0.9696
sub_3:Test (Best Model) - Loss: 0.5225 - Accuracy: 0.9697 - F1: 0.9696
sub_2:Test (Best Model) - Loss: 0.5178 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.9062 - F1: 0.9062
sub_4:Test (Best Model) - Loss: 0.5001 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.5776 - Accuracy: 0.9062 - F1: 0.9062
sub_14:Test (Best Model) - Loss: 0.5438 - Accuracy: 0.9375 - F1: 0.9373
sub_23:Test (Best Model) - Loss: 0.5611 - Accuracy: 0.8750 - F1: 0.8750
sub_11:Test (Best Model) - Loss: 0.5455 - Accuracy: 0.8788 - F1: 0.8787
sub_1:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.8788 - F1: 0.8787
sub_16:Test (Best Model) - Loss: 0.5449 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5310 - Accuracy: 0.8750 - F1: 0.8667
sub_24:Test (Best Model) - Loss: 0.5038 - Accuracy: 0.9688 - F1: 0.9685
sub_10:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.5289 - Accuracy: 0.8788 - F1: 0.8731
sub_7:Test (Best Model) - Loss: 0.5321 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.4754 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.6364 - F1: 0.6071
sub_21:Test (Best Model) - Loss: 0.4930 - Accuracy: 0.9688 - F1: 0.9680
sub_9:Test (Best Model) - Loss: 0.4841 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.4875 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.4893 - Accuracy: 0.9394 - F1: 0.9380
sub_5:Test (Best Model) - Loss: 0.4665 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.4629 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.4286 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.5203 - Accuracy: 0.9688 - F1: 0.9685
sub_8:Test (Best Model) - Loss: 0.5056 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.5375 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.9062 - F1: 0.9062
sub_23:Test (Best Model) - Loss: 0.4830 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.5270 - Accuracy: 0.8788 - F1: 0.8731
sub_4:Test (Best Model) - Loss: 0.5144 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5489 - Accuracy: 0.8125 - F1: 0.8000
sub_3:Test (Best Model) - Loss: 0.5294 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.4895 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4345 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.4878 - Accuracy: 0.9697 - F1: 0.9696
sub_19:Test (Best Model) - Loss: 0.4965 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.4629 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.4426 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.4512 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.4449 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.9688 - F1: 0.9680
sub_16:Test (Best Model) - Loss: 0.5708 - Accuracy: 0.9062 - F1: 0.9062
sub_22:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.7273 - F1: 0.7232
sub_13:Test (Best Model) - Loss: 0.5299 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.4590 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.5188 - Accuracy: 0.8750 - F1: 0.8730
sub_5:Test (Best Model) - Loss: 0.4920 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4494 - Accuracy: 0.9375 - F1: 0.9352
sub_28:Test (Best Model) - Loss: 0.5082 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.5319 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.4434 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.5321 - Accuracy: 0.9688 - F1: 0.9680
sub_15:Test (Best Model) - Loss: 0.4939 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.5194 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 0.4888 - Accuracy: 0.8788 - F1: 0.8731
sub_20:Test (Best Model) - Loss: 0.5037 - Accuracy: 0.8750 - F1: 0.8667
sub_17:Test (Best Model) - Loss: 0.4511 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5342 - Accuracy: 0.9688 - F1: 0.9680
sub_23:Test (Best Model) - Loss: 0.5811 - Accuracy: 0.8788 - F1: 0.8731
sub_24:Test (Best Model) - Loss: 0.4484 - Accuracy: 0.9688 - F1: 0.9685
sub_19:Test (Best Model) - Loss: 0.5216 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.5058 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.4408 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.5318 - Accuracy: 0.9697 - F1: 0.9692
sub_14:Test (Best Model) - Loss: 0.4780 - Accuracy: 0.9375 - F1: 0.9373
sub_11:Test (Best Model) - Loss: 0.5266 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.4703 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.4626 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.5199 - Accuracy: 0.9394 - F1: 0.9380
sub_27:Test (Best Model) - Loss: 0.4511 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.9697 - F1: 0.9692
sub_26:Test (Best Model) - Loss: 0.4433 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5525 - Accuracy: 0.9688 - F1: 0.9680
sub_25:Test (Best Model) - Loss: 0.5134 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.5332 - Accuracy: 0.9091 - F1: 0.9077
sub_6:Test (Best Model) - Loss: 0.4993 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.4393 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5773 - Accuracy: 0.9091 - F1: 0.9060
sub_28:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.8750 - F1: 0.8667
sub_21:Test (Best Model) - Loss: 0.4326 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.4582 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.8788 - F1: 0.8731
sub_2:Test (Best Model) - Loss: 0.5466 - Accuracy: 0.9091 - F1: 0.9060
sub_19:Test (Best Model) - Loss: 0.4522 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.4934 - Accuracy: 0.9697 - F1: 0.9692
sub_9:Test (Best Model) - Loss: 0.4849 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.4473 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.6217 - Accuracy: 0.7188 - F1: 0.7117
sub_24:Test (Best Model) - Loss: 0.5037 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5023 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.4349 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.5157 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.8485 - F1: 0.8479
sub_27:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.5201 - Accuracy: 0.9697 - F1: 0.9692
sub_3:Test (Best Model) - Loss: 0.5248 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.4788 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.5459 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.4692 - Accuracy: 0.9688 - F1: 0.9680
sub_11:Test (Best Model) - Loss: 0.4473 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.5080 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.8125 - F1: 0.8000
sub_25:Test (Best Model) - Loss: 0.5241 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.5022 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.5601 - Accuracy: 0.9688 - F1: 0.9685
sub_28:Test (Best Model) - Loss: 0.6086 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.5039 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5468 - Accuracy: 0.9394 - F1: 0.9380
sub_16:Test (Best Model) - Loss: 0.5984 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.4885 - Accuracy: 0.9394 - F1: 0.9380
sub_2:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.9091 - F1: 0.9060
sub_23:Test (Best Model) - Loss: 0.5465 - Accuracy: 0.8788 - F1: 0.8731
sub_3:Test (Best Model) - Loss: 0.5383 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4458 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.5022 - Accuracy: 0.9688 - F1: 0.9680
sub_15:Test (Best Model) - Loss: 0.4405 - Accuracy: 0.9688 - F1: 0.9680
sub_21:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.6875 - F1: 0.6761
sub_12:Test (Best Model) - Loss: 0.5161 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.5195 - Accuracy: 0.9697 - F1: 0.9696
sub_5:Test (Best Model) - Loss: 0.4589 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.4545 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5411 - Accuracy: 0.8750 - F1: 0.8730
sub_6:Test (Best Model) - Loss: 0.4723 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.5234 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5573 - Accuracy: 0.8750 - F1: 0.8745
sub_9:Test (Best Model) - Loss: 0.4616 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5324 - Accuracy: 0.9062 - F1: 0.9015
sub_11:Test (Best Model) - Loss: 0.4922 - Accuracy: 0.9697 - F1: 0.9696
sub_26:Test (Best Model) - Loss: 0.5005 - Accuracy: 0.9688 - F1: 0.9680
sub_10:Test (Best Model) - Loss: 0.4774 - Accuracy: 0.9394 - F1: 0.9380
sub_25:Test (Best Model) - Loss: 0.4822 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.4584 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.4613 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.8125 - F1: 0.7922
sub_28:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.9375 - F1: 0.9352
sub_20:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.4915 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5992 - Accuracy: 0.8788 - F1: 0.8759
sub_12:Test (Best Model) - Loss: 0.5393 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.5258 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.4962 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 0.4924 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.5055 - Accuracy: 0.8750 - F1: 0.8667
sub_21:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.6875 - F1: 0.6761
sub_5:Test (Best Model) - Loss: 0.4466 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5421 - Accuracy: 0.8750 - F1: 0.8667
sub_3:Test (Best Model) - Loss: 0.5209 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.9375 - F1: 0.9352
sub_4:Test (Best Model) - Loss: 0.5060 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.4984 - Accuracy: 0.9688 - F1: 0.9680
sub_6:Test (Best Model) - Loss: 0.5144 - Accuracy: 0.9697 - F1: 0.9692
sub_7:Test (Best Model) - Loss: 0.5331 - Accuracy: 0.9375 - F1: 0.9365
sub_9:Test (Best Model) - Loss: 0.4745 - Accuracy: 0.9688 - F1: 0.9680
sub_10:Test (Best Model) - Loss: 0.4907 - Accuracy: 0.9394 - F1: 0.9380
sub_26:Test (Best Model) - Loss: 0.4833 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.5982 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.4521 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.8125 - F1: 0.7922
sub_21:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.6250 - F1: 0.6000
sub_25:Test (Best Model) - Loss: 0.5061 - Accuracy: 0.9375 - F1: 0.9352
sub_12:Test (Best Model) - Loss: 0.5415 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.5079 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.4363 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5584 - Accuracy: 0.9091 - F1: 0.9060
sub_17:Test (Best Model) - Loss: 0.5136 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.4598 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.4303 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5821 - Accuracy: 0.8182 - F1: 0.8096
sub_29:Test (Best Model) - Loss: 0.4808 - Accuracy: 0.9697 - F1: 0.9692
sub_11:Test (Best Model) - Loss: 0.4696 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5214 - Accuracy: 0.9062 - F1: 0.9015
sub_15:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.5192 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.8182 - F1: 0.8036
sub_27:Test (Best Model) - Loss: 0.5136 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.9091 - F1: 0.9088
sub_13:Test (Best Model) - Loss: 0.5047 - Accuracy: 0.8750 - F1: 0.8667
sub_3:Test (Best Model) - Loss: 0.5194 - Accuracy: 0.9697 - F1: 0.9692
sub_21:Test (Best Model) - Loss: 0.5785 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.5436 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.8125 - F1: 0.8095
sub_9:Test (Best Model) - Loss: 0.5065 - Accuracy: 0.9062 - F1: 0.9015
sub_22:Test (Best Model) - Loss: 0.5103 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.5352 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.5163 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5131 - Accuracy: 0.8438 - F1: 0.8424
sub_24:Test (Best Model) - Loss: 0.5010 - Accuracy: 0.9375 - F1: 0.9365
sub_10:Test (Best Model) - Loss: 0.5094 - Accuracy: 0.8788 - F1: 0.8731
sub_17:Test (Best Model) - Loss: 0.4886 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.5233 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.5623 - Accuracy: 0.8788 - F1: 0.8731
sub_14:Test (Best Model) - Loss: 0.4919 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5602 - Accuracy: 0.8438 - F1: 0.8303
sub_2:Test (Best Model) - Loss: 0.5722 - Accuracy: 0.8485 - F1: 0.8390
sub_11:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.8788 - F1: 0.8787
sub_13:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.8750 - F1: 0.8667
sub_19:Test (Best Model) - Loss: 0.5447 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.5455 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.4881 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4886 - Accuracy: 0.9688 - F1: 0.9680
sub_3:Test (Best Model) - Loss: 0.5152 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.5261 - Accuracy: 0.9697 - F1: 0.9696
sub_7:Test (Best Model) - Loss: 0.5776 - Accuracy: 0.8750 - F1: 0.8745
sub_21:Test (Best Model) - Loss: 0.5627 - Accuracy: 0.8125 - F1: 0.8118
sub_24:Test (Best Model) - Loss: 0.4919 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.5135 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.4537 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.8750 - F1: 0.8667
sub_7:Test (Best Model) - Loss: 0.5609 - Accuracy: 0.9375 - F1: 0.9373
sub_16:Test (Best Model) - Loss: 0.5330 - Accuracy: 0.8438 - F1: 0.8303
sub_18:Test (Best Model) - Loss: 0.4728 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.5334 - Accuracy: 0.8750 - F1: 0.8704

=== Summary Results ===

acc: 94.65 ± 3.47
F1: 94.46 ± 3.62
acc-in: 96.69 ± 2.67
F1-in: 96.45 ± 2.99
