lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.6905 - F1: 0.6816
sub_1:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.6905 - F1: 0.6816
sub_1:Test (Best Model) - Loss: 0.6106 - Accuracy: 0.6429 - F1: 0.6327
sub_1:Test (Best Model) - Loss: 0.5789 - Accuracy: 0.6905 - F1: 0.6840
sub_1:Test (Best Model) - Loss: 0.6276 - Accuracy: 0.6786 - F1: 0.6748
sub_1:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.7143 - F1: 0.7083
sub_1:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.7143 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.7619 - F1: 0.7597
sub_1:Test (Best Model) - Loss: 0.5198 - Accuracy: 0.7857 - F1: 0.7846
sub_1:Test (Best Model) - Loss: 0.5312 - Accuracy: 0.7738 - F1: 0.7730
sub_1:Test (Best Model) - Loss: 0.5860 - Accuracy: 0.6429 - F1: 0.6050
sub_1:Test (Best Model) - Loss: 0.5425 - Accuracy: 0.6667 - F1: 0.6370
sub_1:Test (Best Model) - Loss: 0.5648 - Accuracy: 0.6667 - F1: 0.6370
sub_1:Test (Best Model) - Loss: 0.5700 - Accuracy: 0.6786 - F1: 0.6473
sub_1:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.6310 - F1: 0.5728
sub_2:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.7143 - F1: 0.6971
sub_2:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.6190 - F1: 0.5634
sub_2:Test (Best Model) - Loss: 0.5984 - Accuracy: 0.7024 - F1: 0.6825
sub_2:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.6071 - F1: 0.5452
sub_2:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.6667 - F1: 0.6370
sub_2:Test (Best Model) - Loss: 0.5422 - Accuracy: 0.6429 - F1: 0.5906
sub_2:Test (Best Model) - Loss: 0.5452 - Accuracy: 0.6310 - F1: 0.5810
sub_2:Test (Best Model) - Loss: 0.5427 - Accuracy: 0.6429 - F1: 0.5906
sub_2:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.6071 - F1: 0.5354
sub_2:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.5357 - F1: 0.4239
sub_2:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.7381 - F1: 0.7224
sub_2:Test (Best Model) - Loss: 0.4867 - Accuracy: 0.8333 - F1: 0.8309
sub_2:Test (Best Model) - Loss: 0.5730 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 0.5130 - Accuracy: 0.7976 - F1: 0.7910
sub_2:Test (Best Model) - Loss: 0.5480 - Accuracy: 0.8095 - F1: 0.8056
sub_3:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.6429 - F1: 0.5982
sub_3:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.6667 - F1: 0.6506
sub_3:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6548 - F1: 0.6212
sub_3:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.5714 - F1: 0.5088
sub_3:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.5833 - F1: 0.5176
sub_3:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.7381 - F1: 0.7368
sub_3:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.6905 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.6548 - F1: 0.6523
sub_3:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.6190 - F1: 0.6082
sub_3:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.6667 - F1: 0.6636
sub_3:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.6905 - F1: 0.6630
sub_3:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.7143 - F1: 0.6971
sub_3:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.7262 - F1: 0.7172
sub_3:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.7143 - F1: 0.7083
sub_3:Test (Best Model) - Loss: 0.5628 - Accuracy: 0.7262 - F1: 0.7040
sub_4:Test (Best Model) - Loss: 0.6190 - Accuracy: 0.6905 - F1: 0.6860
sub_4:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.6310 - F1: 0.6305
sub_4:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.5952 - F1: 0.5894
sub_4:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.6071 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.5952 - F1: 0.5932
sub_4:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.7143 - F1: 0.7035
sub_4:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.7262 - F1: 0.7172
sub_4:Test (Best Model) - Loss: 0.5846 - Accuracy: 0.7143 - F1: 0.7128
sub_4:Test (Best Model) - Loss: 0.6156 - Accuracy: 0.6548 - F1: 0.6317
sub_4:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.6786 - F1: 0.6774
sub_4:Test (Best Model) - Loss: 0.6199 - Accuracy: 0.5952 - F1: 0.5159
sub_4:Test (Best Model) - Loss: 0.6136 - Accuracy: 0.6190 - F1: 0.5544
sub_4:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.5595 - F1: 0.4535
sub_4:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.5833 - F1: 0.5073
sub_4:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.5714 - F1: 0.4875
sub_5:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.7262 - F1: 0.7172
sub_5:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.6905 - F1: 0.6577
sub_5:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.7381 - F1: 0.7255
sub_5:Test (Best Model) - Loss: 0.6143 - Accuracy: 0.7381 - F1: 0.7357
sub_5:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.7381 - F1: 0.7282
sub_5:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.6190 - F1: 0.5634
sub_5:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.5833 - F1: 0.5073
sub_5:Test (Best Model) - Loss: 0.5780 - Accuracy: 0.6548 - F1: 0.6400
sub_5:Test (Best Model) - Loss: 0.5850 - Accuracy: 0.7500 - F1: 0.7393
sub_5:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.5595 - F1: 0.5167
sub_5:Test (Best Model) - Loss: 0.5732 - Accuracy: 0.6786 - F1: 0.6415
sub_5:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.5952 - F1: 0.5265
sub_5:Test (Best Model) - Loss: 0.5767 - Accuracy: 0.7500 - F1: 0.7418
sub_5:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.7500 - F1: 0.7418
sub_5:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.8095 - F1: 0.8056
sub_6:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6071 - F1: 0.5975
sub_6:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5833 - F1: 0.5804
sub_6:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5952 - F1: 0.5950
sub_6:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5714 - F1: 0.5653
sub_6:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.5595 - F1: 0.5407
sub_6:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.6905 - F1: 0.6889
sub_6:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.6071 - F1: 0.5904
sub_6:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5595 - F1: 0.5590
sub_6:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4881 - F1: 0.4863
sub_6:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6310 - F1: 0.6111
sub_6:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.6071 - F1: 0.6003
sub_6:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5714 - F1: 0.5712
sub_6:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.6071 - F1: 0.6003
sub_7:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.6786 - F1: 0.6782
sub_7:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5476 - F1: 0.5411
sub_7:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.6071 - F1: 0.6003
sub_7:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6190 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.5952 - F1: 0.5868
sub_7:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5238 - F1: 0.5102
sub_7:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.5238 - F1: 0.4734
sub_7:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.5595 - F1: 0.5487
sub_7:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.5952 - F1: 0.5524
sub_7:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5476 - F1: 0.4911
sub_7:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4762 - F1: 0.4510
sub_7:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5833 - F1: 0.5655
sub_7:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6190 - F1: 0.6182
sub_7:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.5714 - F1: 0.5592
sub_8:Test (Best Model) - Loss: 0.4592 - Accuracy: 0.7857 - F1: 0.7852
sub_8:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.8095 - F1: 0.8095
sub_8:Test (Best Model) - Loss: 0.4950 - Accuracy: 0.8095 - F1: 0.8095
sub_8:Test (Best Model) - Loss: 0.4715 - Accuracy: 0.7857 - F1: 0.7852
sub_8:Test (Best Model) - Loss: 0.4610 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.4685 - Accuracy: 0.8452 - F1: 0.8442
sub_8:Test (Best Model) - Loss: 0.4866 - Accuracy: 0.8214 - F1: 0.8155
sub_8:Test (Best Model) - Loss: 0.5175 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 0.5068 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 0.4571 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.4677 - Accuracy: 0.7857 - F1: 0.7754
sub_8:Test (Best Model) - Loss: 0.5532 - Accuracy: 0.5833 - F1: 0.4958
sub_8:Test (Best Model) - Loss: 0.5651 - Accuracy: 0.6667 - F1: 0.6313
sub_8:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.7381 - F1: 0.7188
sub_8:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.6905 - F1: 0.6719
sub_9:Test (Best Model) - Loss: 0.5765 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.7619 - F1: 0.7597
sub_9:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.7262 - F1: 0.7243
sub_9:Test (Best Model) - Loss: 0.5693 - Accuracy: 0.7381 - F1: 0.7379
sub_9:Test (Best Model) - Loss: 0.5639 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.6548 - F1: 0.6463
sub_9:Test (Best Model) - Loss: 0.5922 - Accuracy: 0.7024 - F1: 0.7003
sub_9:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.5833 - F1: 0.5761
sub_9:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7381 - F1: 0.7357
sub_9:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6429 - F1: 0.6327
sub_9:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.5952 - F1: 0.5593
sub_9:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.6310 - F1: 0.5884
sub_9:Test (Best Model) - Loss: 0.6309 - Accuracy: 0.6190 - F1: 0.5962
sub_9:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.7262 - F1: 0.7145
sub_9:Test (Best Model) - Loss: 0.5497 - Accuracy: 0.7024 - F1: 0.6783
sub_10:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5952 - F1: 0.5943
sub_10:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.5952 - F1: 0.5943
sub_10:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5476 - F1: 0.5474
sub_10:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6071 - F1: 0.6044
sub_10:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6071 - F1: 0.6026
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.6071 - F1: 0.6044
sub_10:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5595 - F1: 0.5487
sub_10:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5952 - F1: 0.5932
sub_10:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6310 - F1: 0.6245
sub_10:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.5833 - F1: 0.5833
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5595 - F1: 0.5518
sub_10:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6190 - F1: 0.6182
sub_11:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5595 - F1: 0.5238
sub_11:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5833 - F1: 0.5496
sub_11:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.5714 - F1: 0.5625
sub_11:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6190 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.6786 - F1: 0.6748
sub_11:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.6429 - F1: 0.6214
sub_11:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6548 - F1: 0.6268
sub_11:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.6071 - F1: 0.5753
sub_11:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6548 - F1: 0.6400
sub_11:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6310 - F1: 0.6010
sub_11:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.6071 - F1: 0.5753
sub_11:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.5714 - F1: 0.5457
sub_11:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.6429 - F1: 0.6327
sub_11:Test (Best Model) - Loss: 0.6082 - Accuracy: 0.6667 - F1: 0.6619
sub_11:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.6190 - F1: 0.6047
sub_12:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.6667 - F1: 0.6665
sub_12:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.6905 - F1: 0.6840
sub_12:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.6667 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.5603 - Accuracy: 0.7976 - F1: 0.7969
sub_12:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.7143 - F1: 0.7141
sub_12:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.7262 - F1: 0.7243
sub_12:Test (Best Model) - Loss: 0.5602 - Accuracy: 0.7143 - F1: 0.7035
sub_12:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.7143 - F1: 0.7035
sub_12:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.7976 - F1: 0.7962
sub_12:Test (Best Model) - Loss: 0.6314 - Accuracy: 0.6905 - F1: 0.6840
sub_12:Test (Best Model) - Loss: 0.6162 - Accuracy: 0.6190 - F1: 0.5852
sub_12:Test (Best Model) - Loss: 0.5466 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 0.5619 - Accuracy: 0.6786 - F1: 0.6571
sub_12:Test (Best Model) - Loss: 0.5982 - Accuracy: 0.7381 - F1: 0.7368
sub_12:Test (Best Model) - Loss: 0.5756 - Accuracy: 0.7024 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6071 - F1: 0.5942
sub_13:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.7262 - F1: 0.7230
sub_13:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.6548 - F1: 0.6508
sub_13:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5714 - F1: 0.5625
sub_13:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.7262 - F1: 0.7252
sub_13:Test (Best Model) - Loss: 0.6033 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.7738 - F1: 0.7738
sub_13:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.7262 - F1: 0.7262
sub_13:Test (Best Model) - Loss: 0.5803 - Accuracy: 0.7143 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.7619 - F1: 0.7614
sub_13:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.7381 - F1: 0.7379
sub_13:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.7143 - F1: 0.7061
sub_13:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.7143 - F1: 0.7061
sub_14:Test (Best Model) - Loss: 0.5925 - Accuracy: 0.6548 - F1: 0.6212
sub_14:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.6667 - F1: 0.6506
sub_14:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.6310 - F1: 0.5951
sub_14:Test (Best Model) - Loss: 0.5412 - Accuracy: 0.7262 - F1: 0.7252
sub_14:Test (Best Model) - Loss: 0.5352 - Accuracy: 0.7381 - F1: 0.7343
sub_14:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.5952 - F1: 0.5446
sub_14:Test (Best Model) - Loss: 0.5883 - Accuracy: 0.6310 - F1: 0.5951
sub_14:Test (Best Model) - Loss: 0.5170 - Accuracy: 0.7381 - F1: 0.7224
sub_14:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.7500 - F1: 0.7456
sub_14:Test (Best Model) - Loss: 0.5197 - Accuracy: 0.6786 - F1: 0.6525
sub_14:Test (Best Model) - Loss: 0.5944 - Accuracy: 0.6905 - F1: 0.6816
sub_14:Test (Best Model) - Loss: 0.5524 - Accuracy: 0.7262 - F1: 0.7214
sub_14:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.6429 - F1: 0.6050
sub_14:Test (Best Model) - Loss: 0.5920 - Accuracy: 0.7381 - F1: 0.7255
sub_14:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.6786 - F1: 0.6680

=== Summary Results ===

acc: 66.58 ± 5.32
F1: 64.90 ± 5.33
acc-in: 69.45 ± 5.77
F1-in: 68.29 ± 6.09
