lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6106 - Accuracy: 0.7024 - F1: 0.7023
sub_1:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.7143 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 0.5928 - Accuracy: 0.7024 - F1: 0.6989
sub_1:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.6667 - F1: 0.6659
sub_1:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.6190 - F1: 0.6156
sub_1:Test (Best Model) - Loss: 0.6065 - Accuracy: 0.7262 - F1: 0.7214
sub_1:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6548 - F1: 0.6487
sub_1:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.6905 - F1: 0.6903
sub_1:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.7262 - F1: 0.7262
sub_1:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.6429 - F1: 0.6420
sub_1:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.6667 - F1: 0.6421
sub_1:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.7143 - F1: 0.7005
sub_1:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.7024 - F1: 0.6989
sub_1:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.6905 - F1: 0.6677
sub_1:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.6429 - F1: 0.6050
sub_2:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.5595 - F1: 0.4791
sub_2:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6071 - F1: 0.5540
sub_2:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.6905 - F1: 0.6788
sub_2:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.5952 - F1: 0.5265
sub_2:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.6905 - F1: 0.6816
sub_2:Test (Best Model) - Loss: 0.5943 - Accuracy: 0.5952 - F1: 0.5361
sub_2:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.5952 - F1: 0.5361
sub_2:Test (Best Model) - Loss: 0.6106 - Accuracy: 0.6071 - F1: 0.5452
sub_2:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.6667 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.5919 - Accuracy: 0.6905 - F1: 0.6719
sub_2:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.7143 - F1: 0.7083
sub_2:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.7381 - F1: 0.7282
sub_2:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 0.5646 - Accuracy: 0.7143 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.5952 - F1: 0.5524
sub_3:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.6190 - F1: 0.5852
sub_3:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.5833 - F1: 0.5270
sub_3:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.5476 - F1: 0.5074
sub_3:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.6071 - F1: 0.5860
sub_3:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.7143 - F1: 0.7136
sub_3:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.5952 - F1: 0.5932
sub_3:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.5952 - F1: 0.5868
sub_3:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6310 - F1: 0.6267
sub_3:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.6667 - F1: 0.6597
sub_3:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5833 - F1: 0.5804
sub_3:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5952 - F1: 0.5932
sub_3:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.6190 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.6548 - F1: 0.6535
sub_3:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.6190 - F1: 0.6156
sub_4:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5595 - F1: 0.5407
sub_4:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5476 - F1: 0.5435
sub_4:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5476 - F1: 0.5476
sub_4:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5476 - F1: 0.5476
sub_4:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.4881 - F1: 0.4880
sub_4:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.5714 - F1: 0.5457
sub_4:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.6071 - F1: 0.5753
sub_4:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.5952 - F1: 0.5894
sub_4:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6071 - F1: 0.6003
sub_4:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5952 - F1: 0.5159
sub_4:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5833 - F1: 0.5073
sub_4:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.5714 - F1: 0.5088
sub_4:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5357 - F1: 0.4382
sub_4:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.5714 - F1: 0.5179
sub_5:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.7500 - F1: 0.7365
sub_5:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.5714 - F1: 0.4750
sub_5:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.7976 - F1: 0.7962
sub_5:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6310 - F1: 0.6296
sub_5:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6667 - F1: 0.6421
sub_5:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5357 - F1: 0.4729
sub_5:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.5000 - F1: 0.3875
sub_5:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.5476 - F1: 0.5306
sub_5:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.6786 - F1: 0.6680
sub_5:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.6071 - F1: 0.5690
sub_5:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.6667 - F1: 0.6370
sub_5:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.6310 - F1: 0.5884
sub_5:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5595 - F1: 0.5358
sub_5:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.6429 - F1: 0.6166
sub_5:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6667 - F1: 0.6421
sub_6:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5595 - F1: 0.5518
sub_6:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5714 - F1: 0.5675
sub_6:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5357 - F1: 0.5356
sub_6:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5238 - F1: 0.5235
sub_6:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5238 - F1: 0.5009
sub_6:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.4762 - F1: 0.4735
sub_6:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6071 - F1: 0.5904
sub_6:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5476 - F1: 0.5411
sub_6:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.6310 - F1: 0.6245
sub_6:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5595 - F1: 0.5518
sub_6:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.6071 - F1: 0.6003
sub_6:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.5833 - F1: 0.5833
sub_6:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5357 - F1: 0.5303
sub_6:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5833 - F1: 0.5731
sub_7:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5357 - F1: 0.5204
sub_7:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.4762 - F1: 0.4296
sub_7:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.6190 - F1: 0.6156
sub_7:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.5595 - F1: 0.5358
sub_7:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4167 - F1: 0.4024
sub_7:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5000 - F1: 0.4556
sub_7:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.5357 - F1: 0.5204
sub_7:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5238 - F1: 0.5227
sub_7:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5476 - F1: 0.5074
sub_7:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5595 - F1: 0.5088
sub_7:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4643 - F1: 0.4549
sub_7:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5833 - F1: 0.5655
sub_7:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5595 - F1: 0.5302
sub_7:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5357 - F1: 0.4822
sub_8:Test (Best Model) - Loss: 0.6188 - Accuracy: 0.6786 - F1: 0.6648
sub_8:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.6667 - F1: 0.6541
sub_8:Test (Best Model) - Loss: 0.5589 - Accuracy: 0.8214 - F1: 0.8194
sub_8:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.7619 - F1: 0.7529
sub_8:Test (Best Model) - Loss: 0.5784 - Accuracy: 0.7262 - F1: 0.7145
sub_8:Test (Best Model) - Loss: 0.5968 - Accuracy: 0.7500 - F1: 0.7456
sub_8:Test (Best Model) - Loss: 0.5680 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.5869 - Accuracy: 0.7500 - F1: 0.7483
sub_8:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.7857 - F1: 0.7846
sub_8:Test (Best Model) - Loss: 0.5847 - Accuracy: 0.7976 - F1: 0.7953
sub_8:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6071 - F1: 0.5452
sub_8:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6071 - F1: 0.5452
sub_8:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.6310 - F1: 0.5884
sub_8:Test (Best Model) - Loss: 0.5760 - Accuracy: 0.7024 - F1: 0.6735
sub_8:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.6786 - F1: 0.6648
sub_9:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.6905 - F1: 0.6816
sub_9:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.7143 - F1: 0.7083
sub_9:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.7500 - F1: 0.7491
sub_9:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6786 - F1: 0.6707
sub_9:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.6786 - F1: 0.6785
sub_9:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.5952 - F1: 0.5524
sub_9:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6190 - F1: 0.6136
sub_9:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6071 - F1: 0.5942
sub_9:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.6310 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5952 - F1: 0.5943
sub_9:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.6310 - F1: 0.6063
sub_9:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6429 - F1: 0.6050
sub_9:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.6071 - F1: 0.5690
sub_9:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5952 - F1: 0.5868
sub_9:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.6071 - F1: 0.5354
sub_10:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5476 - F1: 0.5453
sub_10:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5238 - F1: 0.5235
sub_10:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.4762 - F1: 0.4687
sub_10:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.5595 - F1: 0.5590
sub_10:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6190 - F1: 0.6007
sub_10:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5357 - F1: 0.5276
sub_10:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5238 - F1: 0.5059
sub_10:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5595 - F1: 0.5595
sub_10:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5476 - F1: 0.5453
sub_10:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5595 - F1: 0.5544
sub_10:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.5357 - F1: 0.5204
sub_10:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6310 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5833 - F1: 0.5731
sub_10:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.5714 - F1: 0.5692
sub_11:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5714 - F1: 0.5457
sub_11:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5238 - F1: 0.4887
sub_11:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.4762 - F1: 0.4750
sub_11:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5476 - F1: 0.5411
sub_11:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.6429 - F1: 0.6294
sub_11:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.6310 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.6071 - F1: 0.6003
sub_11:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.6429 - F1: 0.6294
sub_11:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6667 - F1: 0.6571
sub_11:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.6310 - F1: 0.6267
sub_11:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5238 - F1: 0.5059
sub_11:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5595 - F1: 0.5407
sub_11:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5357 - F1: 0.5204
sub_11:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.5833 - F1: 0.5731
sub_11:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5119 - F1: 0.4911
sub_12:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5833 - F1: 0.5804
sub_12:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5833 - F1: 0.5785
sub_12:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6429 - F1: 0.6257
sub_12:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.7262 - F1: 0.7258
sub_12:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.6786 - F1: 0.6785
sub_12:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.7143 - F1: 0.7102
sub_12:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.6429 - F1: 0.6327
sub_12:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6190 - F1: 0.5962
sub_12:Test (Best Model) - Loss: 0.6237 - Accuracy: 0.7738 - F1: 0.7699
sub_12:Test (Best Model) - Loss: 0.6294 - Accuracy: 0.6310 - F1: 0.6010
sub_12:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.7024 - F1: 0.6863
sub_12:Test (Best Model) - Loss: 0.5910 - Accuracy: 0.6429 - F1: 0.6257
sub_12:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.6905 - F1: 0.6898
sub_12:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.6786 - F1: 0.6680
sub_13:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6429 - F1: 0.6420
sub_13:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.6310 - F1: 0.6152
sub_13:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.6905 - F1: 0.6788
sub_13:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6905 - F1: 0.6860
sub_13:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.5833 - F1: 0.5833
sub_13:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.5833 - F1: 0.5819
sub_13:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.6071 - F1: 0.6044
sub_13:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.7024 - F1: 0.6989
sub_13:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6548 - F1: 0.6361
sub_13:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.6667 - F1: 0.6636
sub_14:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.6548 - F1: 0.6400
sub_14:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.6190 - F1: 0.6007
sub_14:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.6429 - F1: 0.6257
sub_14:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.6786 - F1: 0.6748
sub_14:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.6429 - F1: 0.6214
sub_14:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.5476 - F1: 0.4708
sub_14:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6341 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.6667 - F1: 0.6541
sub_14:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.6667 - F1: 0.6421
sub_14:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.6548 - F1: 0.6463
sub_14:Test (Best Model) - Loss: 0.6484 - Accuracy: 0.5714 - F1: 0.5457
sub_14:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.5952 - F1: 0.5593
sub_14:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.5952 - F1: 0.5894
sub_14:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.6071 - F1: 0.5904

=== Summary Results ===

acc: 62.17 ± 5.28
F1: 60.37 ± 5.40
acc-in: 65.85 ± 4.97
F1-in: 64.63 ± 5.29
