lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6106 - Accuracy: 0.7619 - F1: 0.7504
sub_3:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.5476 - F1: 0.4312
sub_2:Test (Best Model) - Loss: 0.5840 - Accuracy: 0.6905 - F1: 0.6630
sub_2:Test (Best Model) - Loss: 0.5943 - Accuracy: 0.7619 - F1: 0.7569
sub_1:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.7381 - F1: 0.7224
sub_2:Test (Best Model) - Loss: 0.5993 - Accuracy: 0.6429 - F1: 0.5906
sub_3:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5906 - Accuracy: 0.6310 - F1: 0.5728
sub_3:Test (Best Model) - Loss: 0.7981 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.6071 - F1: 0.5354
sub_2:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.6667 - F1: 0.6313
sub_3:Test (Best Model) - Loss: 0.8884 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5119 - F1: 0.3593
sub_2:Test (Best Model) - Loss: 0.4642 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5233 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.7976 - F1: 0.7941
sub_3:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.5714 - F1: 0.4987
sub_2:Test (Best Model) - Loss: 0.4766 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.8333 - F1: 0.8332
sub_3:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6620 - Accuracy: 0.8095 - F1: 0.8056
sub_2:Test (Best Model) - Loss: 0.4783 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5119 - F1: 0.3778
sub_2:Test (Best Model) - Loss: 0.5308 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.8214 - F1: 0.8183
sub_3:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.5119 - F1: 0.3778
sub_2:Test (Best Model) - Loss: 1.0916 - Accuracy: 0.5357 - F1: 0.4822
sub_1:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.8333 - F1: 0.8330
sub_2:Test (Best Model) - Loss: 0.8330 - Accuracy: 0.7976 - F1: 0.7969
sub_3:Test (Best Model) - Loss: 0.8574 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.9523 - Accuracy: 0.8333 - F1: 0.8309
sub_2:Test (Best Model) - Loss: 1.0109 - Accuracy: 0.5833 - F1: 0.5496
sub_3:Test (Best Model) - Loss: 0.9218 - Accuracy: 0.7500 - F1: 0.7393
sub_1:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.7738 - F1: 0.7735
sub_3:Test (Best Model) - Loss: 1.1681 - Accuracy: 0.5238 - F1: 0.5009
sub_2:Test (Best Model) - Loss: 1.4487 - Accuracy: 0.5595 - F1: 0.4901
sub_2:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.7738 - F1: 0.7730
sub_1:Test (Best Model) - Loss: 0.7408 - Accuracy: 0.7857 - F1: 0.7846
sub_3:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.7500 - F1: 0.7365
sub_1:Test (Best Model) - Loss: 0.8618 - Accuracy: 0.7262 - F1: 0.7145
sub_3:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.7262 - F1: 0.7195
sub_1:Test (Best Model) - Loss: 0.5119 - Accuracy: 0.7857 - F1: 0.7826
sub_4:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.7500 - F1: 0.7365
sub_5:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.5833 - F1: 0.5270
sub_6:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.7143 - F1: 0.6889
sub_5:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.5952 - F1: 0.5265
sub_5:Test (Best Model) - Loss: 0.6055 - Accuracy: 0.5952 - F1: 0.5361
sub_4:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 0.6087 - Accuracy: 0.7024 - F1: 0.6989
sub_6:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.6786 - F1: 0.6473
sub_4:Test (Best Model) - Loss: 0.7279 - Accuracy: 0.7500 - F1: 0.7365
sub_5:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.7500 - F1: 0.7500
sub_6:Test (Best Model) - Loss: 0.5682 - Accuracy: 0.7738 - F1: 0.7641
sub_4:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.7857 - F1: 0.7796
sub_5:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.6905 - F1: 0.6577
sub_6:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.6272 - Accuracy: 0.7500 - F1: 0.7365
sub_6:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.6786 - F1: 0.6415
sub_4:Test (Best Model) - Loss: 0.5641 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 0.7453 - Accuracy: 0.7500 - F1: 0.7439
sub_6:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.7262 - F1: 0.7195
sub_5:Test (Best Model) - Loss: 0.6139 - Accuracy: 0.7262 - F1: 0.7145
sub_6:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.6905 - F1: 0.6816
sub_4:Test (Best Model) - Loss: 0.5382 - Accuracy: 0.8571 - F1: 0.8571
sub_5:Test (Best Model) - Loss: 0.5862 - Accuracy: 0.7976 - F1: 0.7941
sub_4:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.7143 - F1: 0.6932
sub_6:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.7262 - F1: 0.7040
sub_4:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.8095 - F1: 0.8041
sub_5:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.7262 - F1: 0.7079
sub_6:Test (Best Model) - Loss: 0.7457 - Accuracy: 0.5238 - F1: 0.5139
sub_5:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.5476 - F1: 0.4312
sub_6:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.5357 - F1: 0.5204
sub_4:Test (Best Model) - Loss: 0.5988 - Accuracy: 0.8929 - F1: 0.8927
sub_5:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5119 - F1: 0.3778
sub_4:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.7143 - F1: 0.7061
sub_6:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.5714 - F1: 0.5399
sub_4:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.7381 - F1: 0.7379
sub_6:Test (Best Model) - Loss: 0.7764 - Accuracy: 0.4643 - F1: 0.4624
sub_5:Test (Best Model) - Loss: 0.5105 - Accuracy: 0.7857 - F1: 0.7852
sub_4:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6190 - F1: 0.6007
sub_6:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.5595 - F1: 0.5167
sub_4:Test (Best Model) - Loss: 0.7440 - Accuracy: 0.5833 - F1: 0.5609
sub_4:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.7381 - F1: 0.7379
sub_7:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.6548 - F1: 0.6400
sub_8:Test (Best Model) - Loss: 0.4460 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.6786 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 0.4791 - Accuracy: 0.7976 - F1: 0.7910
sub_8:Test (Best Model) - Loss: 0.5164 - Accuracy: 0.7619 - F1: 0.7476
sub_7:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.5274 - Accuracy: 0.9286 - F1: 0.9285
sub_9:Test (Best Model) - Loss: 0.4430 - Accuracy: 0.7619 - F1: 0.7504
sub_7:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.5119 - F1: 0.3593
sub_7:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.6667 - F1: 0.6571
sub_8:Test (Best Model) - Loss: 0.5154 - Accuracy: 0.9167 - F1: 0.9166
sub_9:Test (Best Model) - Loss: 0.4578 - Accuracy: 0.7381 - F1: 0.7188
sub_7:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.6905 - F1: 0.6860
sub_8:Test (Best Model) - Loss: 0.4347 - Accuracy: 0.9167 - F1: 0.9164
sub_7:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6190 - F1: 0.5634
sub_8:Test (Best Model) - Loss: 0.4768 - Accuracy: 0.9048 - F1: 0.9047
sub_9:Test (Best Model) - Loss: 0.4917 - Accuracy: 0.6310 - F1: 0.5728
sub_7:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.5714 - F1: 0.4987
sub_8:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.4771 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.6310 - F1: 0.5728
sub_8:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.9048 - F1: 0.9048
sub_9:Test (Best Model) - Loss: 0.4267 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.4250 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.7334 - Accuracy: 0.6310 - F1: 0.6152
sub_9:Test (Best Model) - Loss: 0.4351 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 0.4891 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.4844 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5952 - F1: 0.5915
sub_9:Test (Best Model) - Loss: 0.4432 - Accuracy: 0.7976 - F1: 0.7927
sub_8:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.8571 - F1: 0.8551
sub_7:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.6190 - F1: 0.6156
sub_9:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.6905 - F1: 0.6905
sub_8:Test (Best Model) - Loss: 0.4421 - Accuracy: 0.7857 - F1: 0.7754
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5833 - F1: 0.5833
sub_8:Test (Best Model) - Loss: 0.4822 - Accuracy: 0.8810 - F1: 0.8799
sub_7:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5357 - F1: 0.5159
sub_9:Test (Best Model) - Loss: 0.4437 - Accuracy: 0.8929 - F1: 0.8928
sub_8:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 0.5423 - Accuracy: 0.7381 - F1: 0.7255
sub_9:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.6310 - F1: 0.6111
sub_9:Test (Best Model) - Loss: 0.5848 - Accuracy: 0.6786 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 0.8903 - Accuracy: 0.5952 - F1: 0.5800
sub_11:Test (Best Model) - Loss: 0.5492 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.8452 - F1: 0.8452
sub_10:Test (Best Model) - Loss: 0.5047 - Accuracy: 0.7976 - F1: 0.7962
sub_11:Test (Best Model) - Loss: 0.5465 - Accuracy: 0.8929 - F1: 0.8927
sub_12:Test (Best Model) - Loss: 0.6510 - Accuracy: 0.6905 - F1: 0.6719
sub_10:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6905 - F1: 0.6876
sub_11:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.7976 - F1: 0.7941
sub_10:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.7143 - F1: 0.7143
sub_12:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.7857 - F1: 0.7846
sub_11:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.7738 - F1: 0.7616
sub_10:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.6310 - F1: 0.6188
sub_12:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.8214 - F1: 0.8212
sub_11:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.8333 - F1: 0.8299
sub_10:Test (Best Model) - Loss: 0.5732 - Accuracy: 0.6310 - F1: 0.6010
sub_11:Test (Best Model) - Loss: 0.3703 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.7568 - Accuracy: 0.5119 - F1: 0.4958
sub_10:Test (Best Model) - Loss: 0.5219 - Accuracy: 0.7976 - F1: 0.7976
sub_12:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.4762 - F1: 0.4376
sub_11:Test (Best Model) - Loss: 0.3519 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.5743 - Accuracy: 0.7976 - F1: 0.7976
sub_12:Test (Best Model) - Loss: 0.7415 - Accuracy: 0.5238 - F1: 0.5139
sub_11:Test (Best Model) - Loss: 0.4165 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.7500 - F1: 0.7491
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.6190 - F1: 0.6182
sub_11:Test (Best Model) - Loss: 0.4703 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.5360 - Accuracy: 0.8333 - F1: 0.8318
sub_12:Test (Best Model) - Loss: 0.7774 - Accuracy: 0.4643 - F1: 0.4466
sub_11:Test (Best Model) - Loss: 0.3625 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.5724 - Accuracy: 0.8333 - F1: 0.8325
sub_12:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.8929 - F1: 0.8925
sub_11:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.7857 - F1: 0.7852
sub_10:Test (Best Model) - Loss: 0.5593 - Accuracy: 0.6310 - F1: 0.5810
sub_11:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.7738 - F1: 0.7735
sub_12:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6905 - F1: 0.6577
sub_10:Test (Best Model) - Loss: 0.5160 - Accuracy: 0.6905 - F1: 0.6630
sub_12:Test (Best Model) - Loss: 0.5161 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.6667 - F1: 0.6619
sub_10:Test (Best Model) - Loss: 0.5752 - Accuracy: 0.5476 - F1: 0.4458
sub_12:Test (Best Model) - Loss: 0.8530 - Accuracy: 0.5238 - F1: 0.3842
sub_11:Test (Best Model) - Loss: 0.6052 - Accuracy: 0.7857 - F1: 0.7857
sub_12:Test (Best Model) - Loss: 1.0976 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7280 - Accuracy: 0.5595 - F1: 0.4670
sub_11:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.7262 - F1: 0.7243
sub_10:Test (Best Model) - Loss: 0.5416 - Accuracy: 0.6429 - F1: 0.5982
sub_14:Test (Best Model) - Loss: 0.5503 - Accuracy: 0.8095 - F1: 0.8041
sub_13:Test (Best Model) - Loss: 0.5693 - Accuracy: 0.8929 - F1: 0.8925
sub_14:Test (Best Model) - Loss: 0.4722 - Accuracy: 0.7738 - F1: 0.7616
sub_13:Test (Best Model) - Loss: 0.5988 - Accuracy: 0.8810 - F1: 0.8809
sub_14:Test (Best Model) - Loss: 0.5485 - Accuracy: 0.8452 - F1: 0.8434
sub_13:Test (Best Model) - Loss: 0.6125 - Accuracy: 0.7857 - F1: 0.7796
sub_14:Test (Best Model) - Loss: 0.4811 - Accuracy: 0.8095 - F1: 0.8041
sub_13:Test (Best Model) - Loss: 0.6014 - Accuracy: 0.5595 - F1: 0.4535
sub_14:Test (Best Model) - Loss: 0.5007 - Accuracy: 0.7738 - F1: 0.7616
sub_13:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.6548 - F1: 0.6080
sub_14:Test (Best Model) - Loss: 0.6096 - Accuracy: 0.7976 - F1: 0.7890
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.7976 - F1: 0.7974
sub_14:Test (Best Model) - Loss: 0.4629 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.5347 - Accuracy: 0.8095 - F1: 0.8068
sub_14:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.8333 - F1: 0.8286
sub_13:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 0.6123 - Accuracy: 0.8929 - F1: 0.8921
sub_13:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.7976 - F1: 0.7969
sub_14:Test (Best Model) - Loss: 0.5753 - Accuracy: 0.9048 - F1: 0.9043
sub_13:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.7976 - F1: 0.7974
sub_14:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.5952 - F1: 0.5361
sub_14:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.5357 - F1: 0.4081
sub_13:Test (Best Model) - Loss: 0.4373 - Accuracy: 0.8810 - F1: 0.8809
sub_14:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.5714 - F1: 0.5088
sub_14:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.5000 - F1: 0.4375
sub_13:Test (Best Model) - Loss: 0.4794 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5119 - F1: 0.3944
sub_13:Test (Best Model) - Loss: 0.5328 - Accuracy: 0.8810 - F1: 0.8807
sub_13:Test (Best Model) - Loss: 0.5531 - Accuracy: 0.8929 - F1: 0.8928
sub_13:Test (Best Model) - Loss: 0.3569 - Accuracy: 0.8571 - F1: 0.8564

=== Summary Results ===

acc: 72.66 ± 8.42
F1: 69.92 ± 10.27
acc-in: 81.08 ± 7.75
F1-in: 79.95 ± 8.80
runing time: 1074.29 seconds
