lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6429 - F1: 0.6396
sub_1:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.6548 - F1: 0.6487
sub_1:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.6429 - F1: 0.6396
sub_1:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.6190 - F1: 0.6171
sub_1:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.6190 - F1: 0.6171
sub_1:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.6786 - F1: 0.6730
sub_1:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6548 - F1: 0.6508
sub_1:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.7024 - F1: 0.6989
sub_1:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.6786 - F1: 0.6782
sub_1:Test (Best Model) - Loss: 0.6223 - Accuracy: 0.6667 - F1: 0.6650
sub_1:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.6071 - F1: 0.5753
sub_1:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.5714 - F1: 0.5333
sub_1:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.6071 - F1: 0.5904
sub_1:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.6310 - F1: 0.6111
sub_1:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6190 - F1: 0.5852
sub_2:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.7143 - F1: 0.7061
sub_2:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.6071 - F1: 0.5540
sub_2:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.6548 - F1: 0.6361
sub_2:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.5833 - F1: 0.5556
sub_2:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.5952 - F1: 0.5593
sub_2:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.5952 - F1: 0.5446
sub_2:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.6548 - F1: 0.6400
sub_2:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6310 - F1: 0.6010
sub_2:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.6190 - F1: 0.5910
sub_2:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.5952 - F1: 0.5446
sub_2:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.6667 - F1: 0.6619
sub_2:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.7024 - F1: 0.6972
sub_2:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.6786 - F1: 0.6748
sub_2:Test (Best Model) - Loss: 0.6274 - Accuracy: 0.6905 - F1: 0.6905
sub_2:Test (Best Model) - Loss: 0.6236 - Accuracy: 0.6429 - F1: 0.6410
sub_3:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5833 - F1: 0.5270
sub_3:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6190 - F1: 0.5962
sub_3:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.6071 - F1: 0.5753
sub_3:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5119 - F1: 0.4645
sub_3:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5000 - F1: 0.4896
sub_3:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.7024 - F1: 0.6989
sub_3:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5119 - F1: 0.5113
sub_3:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5238 - F1: 0.5139
sub_3:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6071 - F1: 0.6003
sub_3:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6071 - F1: 0.6044
sub_3:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5714 - F1: 0.5714
sub_3:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6190 - F1: 0.6171
sub_3:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6190 - F1: 0.6188
sub_3:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5595 - F1: 0.5590
sub_3:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.5595 - F1: 0.5595
sub_4:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5476 - F1: 0.5466
sub_4:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5833 - F1: 0.5785
sub_4:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4881 - F1: 0.4863
sub_4:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5119 - F1: 0.5085
sub_4:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5238 - F1: 0.5235
sub_4:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.4881 - F1: 0.4383
sub_4:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5595 - F1: 0.5518
sub_4:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.6071 - F1: 0.6044
sub_4:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.6071 - F1: 0.6026
sub_4:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.5476 - F1: 0.5411
sub_4:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5357 - F1: 0.4382
sub_4:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5833 - F1: 0.5428
sub_4:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5476 - F1: 0.4708
sub_4:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5714 - F1: 0.5260
sub_4:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6071 - F1: 0.5690
sub_5:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5952 - F1: 0.5943
sub_5:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.5595 - F1: 0.4670
sub_5:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5952 - F1: 0.5709
sub_5:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5952 - F1: 0.5943
sub_5:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.5833 - F1: 0.5073
sub_5:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5000 - F1: 0.4151
sub_5:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5119 - F1: 0.4645
sub_5:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5833 - F1: 0.5785
sub_5:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5833 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.5238 - F1: 0.4643
sub_5:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5952 - F1: 0.5593
sub_5:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5476 - F1: 0.4997
sub_5:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6667 - F1: 0.6541
sub_5:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5238 - F1: 0.5059
sub_5:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5238 - F1: 0.5102
sub_6:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5714 - F1: 0.5712
sub_6:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5238 - F1: 0.4887
sub_6:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4881 - F1: 0.4845
sub_6:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5952 - F1: 0.5932
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.4881 - F1: 0.4712
sub_6:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5476 - F1: 0.5347
sub_6:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5476 - F1: 0.5258
sub_6:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5357 - F1: 0.5303
sub_6:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5119 - F1: 0.4794
sub_6:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5238 - F1: 0.5102
sub_6:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5833 - F1: 0.5785
sub_6:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4762 - F1: 0.4759
sub_6:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5476 - F1: 0.5382
sub_7:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6310 - F1: 0.6219
sub_7:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4405 - F1: 0.3760
sub_7:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5357 - F1: 0.5243
sub_7:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.5238 - F1: 0.5170
sub_7:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6071 - F1: 0.5753
sub_7:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.4762 - F1: 0.4510
sub_7:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5714 - F1: 0.5260
sub_7:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.4762 - F1: 0.4565
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5238 - F1: 0.5235
sub_7:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5952 - F1: 0.5593
sub_7:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5714 - F1: 0.5592
sub_7:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5357 - F1: 0.5204
sub_7:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5833 - F1: 0.5696
sub_7:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5476 - F1: 0.5306
sub_7:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5357 - F1: 0.5243
sub_8:Test (Best Model) - Loss: 0.5994 - Accuracy: 0.7262 - F1: 0.7214
sub_8:Test (Best Model) - Loss: 0.6509 - Accuracy: 0.6429 - F1: 0.6294
sub_8:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.7262 - F1: 0.7172
sub_8:Test (Best Model) - Loss: 0.6219 - Accuracy: 0.7381 - F1: 0.7375
sub_8:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.6905 - F1: 0.6756
sub_8:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.7262 - F1: 0.7230
sub_8:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6429 - F1: 0.6166
sub_8:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.6786 - F1: 0.6748
sub_8:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.7143 - F1: 0.7117
sub_8:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.7500 - F1: 0.7456
sub_8:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.5357 - F1: 0.4510
sub_8:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.5595 - F1: 0.4670
sub_8:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.6667 - F1: 0.6571
sub_8:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.6429 - F1: 0.6166
sub_8:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.5476 - F1: 0.5074
sub_9:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6667 - F1: 0.6650
sub_9:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.6548 - F1: 0.6400
sub_9:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5357 - F1: 0.5159
sub_9:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5476 - F1: 0.5382
sub_9:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.6429 - F1: 0.6294
sub_9:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5476 - F1: 0.5258
sub_9:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6071 - F1: 0.6026
sub_9:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5714 - F1: 0.5592
sub_9:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4881 - F1: 0.4845
sub_9:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5357 - F1: 0.5276
sub_9:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5595 - F1: 0.5564
sub_9:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.5952 - F1: 0.5800
sub_9:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5357 - F1: 0.5204
sub_9:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.6190 - F1: 0.6082
sub_9:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6548 - F1: 0.6080
sub_10:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5357 - F1: 0.5356
sub_10:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5238 - F1: 0.5227
sub_10:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.4881 - F1: 0.4863
sub_10:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5000 - F1: 0.4954
sub_10:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5714 - F1: 0.5714
sub_10:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.6190 - F1: 0.6082
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.5351
sub_10:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5476 - F1: 0.5453
sub_10:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5238 - F1: 0.5227
sub_10:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.5952 - F1: 0.5915
sub_10:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5476 - F1: 0.5435
sub_10:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6667 - F1: 0.6650
sub_10:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5238 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6548 - F1: 0.6523
sub_11:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5476 - F1: 0.5435
sub_11:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4881 - F1: 0.4383
sub_11:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5000 - F1: 0.4954
sub_11:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.5476 - F1: 0.5466
sub_11:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5714 - F1: 0.5457
sub_11:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5952 - F1: 0.5593
sub_11:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.5833 - F1: 0.5828
sub_11:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.6905 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6310 - F1: 0.6305
sub_11:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6071 - F1: 0.5975
sub_11:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5000 - F1: 0.4812
sub_11:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.5357 - F1: 0.5303
sub_11:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4762 - F1: 0.4714
sub_11:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5119 - F1: 0.4999
sub_11:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5595 - F1: 0.5487
sub_12:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.5952 - F1: 0.5915
sub_12:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5357 - F1: 0.5341
sub_12:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.6429 - F1: 0.6427
sub_12:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6786 - F1: 0.6782
sub_12:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6071 - F1: 0.6071
sub_12:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.7381 - F1: 0.7368
sub_12:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6905 - F1: 0.6876
sub_12:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6548 - F1: 0.6434
sub_12:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.6667 - F1: 0.6665
sub_12:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6667 - F1: 0.6571
sub_12:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5238 - F1: 0.4887
sub_12:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5952 - F1: 0.5837
sub_12:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.5595 - F1: 0.5518
sub_12:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.6190 - F1: 0.6082
sub_12:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.6310 - F1: 0.6188
sub_13:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6429 - F1: 0.6410
sub_13:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6905 - F1: 0.6898
sub_13:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5714 - F1: 0.5653
sub_13:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5714 - F1: 0.5553
sub_13:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6429 - F1: 0.6420
sub_13:Test (Best Model) - Loss: 0.6414 - Accuracy: 0.6667 - F1: 0.6665
sub_13:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.6786 - F1: 0.6748
sub_13:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.6548 - F1: 0.6543
sub_13:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.6071 - F1: 0.5975
sub_13:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.6071 - F1: 0.5753
sub_13:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.7262 - F1: 0.7252
sub_14:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.6310 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6190 - F1: 0.6007
sub_14:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6667 - F1: 0.6541
sub_14:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.6667 - F1: 0.6650
sub_14:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.6310 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.5952 - F1: 0.5837
sub_14:Test (Best Model) - Loss: 0.6371 - Accuracy: 0.6071 - F1: 0.5753
sub_14:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6548 - F1: 0.6508
sub_14:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.5714 - F1: 0.5260
sub_14:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.5714 - F1: 0.5592
sub_14:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6429 - F1: 0.6354
sub_14:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.5952 - F1: 0.5758
sub_14:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.5595 - F1: 0.5407
sub_14:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.6190 - F1: 0.6082

=== Summary Results ===

acc: 59.45 ± 4.22
F1: 57.87 ± 4.41
acc-in: 64.44 ± 5.57
F1-in: 63.52 ± 5.73
