lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.6905 - F1: 0.6860
sub_1:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.6667 - F1: 0.6506
sub_1:Test (Best Model) - Loss: 0.5607 - Accuracy: 0.7024 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.5660 - Accuracy: 0.7024 - F1: 0.6926
sub_1:Test (Best Model) - Loss: 0.5659 - Accuracy: 0.6905 - F1: 0.6756
sub_1:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.6905 - F1: 0.6860
sub_1:Test (Best Model) - Loss: 0.5158 - Accuracy: 0.7500 - F1: 0.7439
sub_1:Test (Best Model) - Loss: 0.5774 - Accuracy: 0.7381 - F1: 0.7343
sub_1:Test (Best Model) - Loss: 0.5267 - Accuracy: 0.7619 - F1: 0.7614
sub_1:Test (Best Model) - Loss: 0.4425 - Accuracy: 0.8333 - F1: 0.8325
sub_1:Test (Best Model) - Loss: 0.5489 - Accuracy: 0.6786 - F1: 0.6473
sub_1:Test (Best Model) - Loss: 0.5770 - Accuracy: 0.6786 - F1: 0.6525
sub_1:Test (Best Model) - Loss: 0.5204 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 0.5381 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 0.5544 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 0.5567 - Accuracy: 0.7738 - F1: 0.7712
sub_2:Test (Best Model) - Loss: 0.5632 - Accuracy: 0.7143 - F1: 0.7117
sub_2:Test (Best Model) - Loss: 0.5762 - Accuracy: 0.7024 - F1: 0.6989
sub_2:Test (Best Model) - Loss: 0.5822 - Accuracy: 0.7976 - F1: 0.7974
sub_2:Test (Best Model) - Loss: 0.5205 - Accuracy: 0.7500 - F1: 0.7483
sub_2:Test (Best Model) - Loss: 0.5142 - Accuracy: 0.7143 - F1: 0.7035
sub_2:Test (Best Model) - Loss: 0.4861 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 0.5080 - Accuracy: 0.7500 - F1: 0.7365
sub_2:Test (Best Model) - Loss: 0.4925 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.5398 - Accuracy: 0.6429 - F1: 0.5982
sub_2:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.6905 - F1: 0.6905
sub_2:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.6667 - F1: 0.6665
sub_2:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.7024 - F1: 0.7003
sub_2:Test (Best Model) - Loss: 0.4298 - Accuracy: 0.8095 - F1: 0.8095
sub_2:Test (Best Model) - Loss: 0.5222 - Accuracy: 0.7262 - F1: 0.7258
sub_3:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.6190 - F1: 0.5787
sub_3:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.6071 - F1: 0.5540
sub_3:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.5833 - F1: 0.5073
sub_3:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.6071 - F1: 0.5690
sub_3:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6071 - F1: 0.5354
sub_3:Test (Best Model) - Loss: 0.5588 - Accuracy: 0.7262 - F1: 0.7262
sub_3:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.6667 - F1: 0.6636
sub_3:Test (Best Model) - Loss: 0.5551 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 0.5230 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 0.5534 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6786 - F1: 0.6415
sub_3:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.6071 - F1: 0.5354
sub_3:Test (Best Model) - Loss: 0.5841 - Accuracy: 0.7262 - F1: 0.7079
sub_3:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.6310 - F1: 0.5951
sub_3:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.6905 - F1: 0.6577
sub_4:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.6310 - F1: 0.6296
sub_4:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.5952 - F1: 0.5952
sub_4:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5714 - F1: 0.5712
sub_4:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5714 - F1: 0.5705
sub_4:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.6071 - F1: 0.6066
sub_4:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.5595 - F1: 0.5487
sub_4:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.5952 - F1: 0.5868
sub_4:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.6667 - F1: 0.6619
sub_4:Test (Best Model) - Loss: 0.5931 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.5833 - F1: 0.5785
sub_4:Test (Best Model) - Loss: 0.5822 - Accuracy: 0.7381 - F1: 0.7326
sub_4:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.6786 - F1: 0.6707
sub_4:Test (Best Model) - Loss: 0.5619 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.6548 - F1: 0.6463
sub_4:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.6548 - F1: 0.6434
sub_5:Test (Best Model) - Loss: 0.5258 - Accuracy: 0.7262 - F1: 0.7262
sub_5:Test (Best Model) - Loss: 0.5194 - Accuracy: 0.7619 - F1: 0.7597
sub_5:Test (Best Model) - Loss: 0.5657 - Accuracy: 0.7738 - F1: 0.7730
sub_5:Test (Best Model) - Loss: 0.5424 - Accuracy: 0.7381 - F1: 0.7375
sub_5:Test (Best Model) - Loss: 0.5256 - Accuracy: 0.7619 - F1: 0.7585
sub_5:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.6786 - F1: 0.6648
sub_5:Test (Best Model) - Loss: 0.6184 - Accuracy: 0.6548 - F1: 0.6317
sub_5:Test (Best Model) - Loss: 0.5415 - Accuracy: 0.6905 - F1: 0.6898
sub_5:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.7143 - F1: 0.7083
sub_5:Test (Best Model) - Loss: 0.5880 - Accuracy: 0.6905 - F1: 0.6860
sub_5:Test (Best Model) - Loss: 0.5841 - Accuracy: 0.7024 - F1: 0.6951
sub_5:Test (Best Model) - Loss: 0.5403 - Accuracy: 0.7262 - F1: 0.7214
sub_5:Test (Best Model) - Loss: 0.4429 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 0.5159 - Accuracy: 0.7619 - F1: 0.7569
sub_5:Test (Best Model) - Loss: 0.4816 - Accuracy: 0.7738 - F1: 0.7735
sub_6:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5595 - F1: 0.5590
sub_6:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.5714 - F1: 0.5675
sub_6:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5952 - F1: 0.5950
sub_6:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5714 - F1: 0.5714
sub_6:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.5833 - F1: 0.5696
sub_6:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.6429 - F1: 0.6396
sub_6:Test (Best Model) - Loss: 0.6133 - Accuracy: 0.6667 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.5595 - F1: 0.5595
sub_6:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.6905 - F1: 0.6903
sub_7:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5119 - F1: 0.4999
sub_7:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5714 - F1: 0.5705
sub_7:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5595 - F1: 0.5564
sub_7:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4643 - F1: 0.4511
sub_7:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.5714 - F1: 0.5399
sub_7:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.4405 - F1: 0.4166
sub_7:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5476 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6190 - F1: 0.5962
sub_7:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.5119 - F1: 0.5062
sub_7:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.6429 - F1: 0.6410
sub_7:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5357 - F1: 0.5356
sub_7:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5714 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 0.4179 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.4044 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.3933 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.4049 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.4353 - Accuracy: 0.7976 - F1: 0.7969
sub_8:Test (Best Model) - Loss: 0.4580 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.4661 - Accuracy: 0.7976 - F1: 0.7941
sub_8:Test (Best Model) - Loss: 0.4448 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.3781 - Accuracy: 0.8333 - F1: 0.8330
sub_8:Test (Best Model) - Loss: 0.4117 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.4324 - Accuracy: 0.8214 - F1: 0.8194
sub_8:Test (Best Model) - Loss: 0.4505 - Accuracy: 0.7976 - F1: 0.7910
sub_8:Test (Best Model) - Loss: 0.4242 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.4492 - Accuracy: 0.8095 - F1: 0.8078
sub_8:Test (Best Model) - Loss: 0.4535 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.4411 - Accuracy: 0.7619 - F1: 0.7597
sub_9:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.7024 - F1: 0.7020
sub_9:Test (Best Model) - Loss: 0.4690 - Accuracy: 0.7857 - F1: 0.7826
sub_9:Test (Best Model) - Loss: 0.5797 - Accuracy: 0.7262 - F1: 0.7258
sub_9:Test (Best Model) - Loss: 0.5361 - Accuracy: 0.7381 - F1: 0.7368
sub_9:Test (Best Model) - Loss: 0.4741 - Accuracy: 0.7857 - F1: 0.7852
sub_9:Test (Best Model) - Loss: 0.5545 - Accuracy: 0.7262 - F1: 0.7243
sub_9:Test (Best Model) - Loss: 0.5647 - Accuracy: 0.7262 - F1: 0.7252
sub_9:Test (Best Model) - Loss: 0.4978 - Accuracy: 0.7381 - F1: 0.7375
sub_9:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.7143 - F1: 0.7128
sub_9:Test (Best Model) - Loss: 0.5757 - Accuracy: 0.6905 - F1: 0.6630
sub_9:Test (Best Model) - Loss: 0.5095 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.5192 - Accuracy: 0.7262 - F1: 0.7079
sub_9:Test (Best Model) - Loss: 0.4933 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.5228 - Accuracy: 0.6905 - F1: 0.6577
sub_10:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.6548 - F1: 0.6547
sub_10:Test (Best Model) - Loss: 0.5997 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.5714 - F1: 0.5705
sub_10:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.6071 - F1: 0.6026
sub_10:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.6429 - F1: 0.6427
sub_10:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.6905 - F1: 0.6903
sub_10:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.6429 - F1: 0.6396
sub_10:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5714 - F1: 0.5705
sub_10:Test (Best Model) - Loss: 0.6223 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 0.6341 - Accuracy: 0.6786 - F1: 0.6782
sub_10:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.5952 - F1: 0.5932
sub_10:Test (Best Model) - Loss: 0.5923 - Accuracy: 0.7143 - F1: 0.7102
sub_10:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6310 - F1: 0.6188
sub_10:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.6429 - F1: 0.6420
sub_11:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6429 - F1: 0.6429
sub_11:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.5714 - F1: 0.5675
sub_11:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.6190 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5714 - F1: 0.5714
sub_11:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6071 - F1: 0.6066
sub_11:Test (Best Model) - Loss: 0.5171 - Accuracy: 0.7619 - F1: 0.7618
sub_11:Test (Best Model) - Loss: 0.5333 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.5908 - Accuracy: 0.7143 - F1: 0.7136
sub_11:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.6786 - F1: 0.6774
sub_11:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.6190 - F1: 0.6182
sub_11:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.5714 - F1: 0.5653
sub_11:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5476 - F1: 0.5476
sub_11:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.6071 - F1: 0.6071
sub_11:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.6548 - F1: 0.6543
sub_12:Test (Best Model) - Loss: 0.6065 - Accuracy: 0.6548 - F1: 0.6543
sub_12:Test (Best Model) - Loss: 0.5555 - Accuracy: 0.7500 - F1: 0.7439
sub_12:Test (Best Model) - Loss: 0.4972 - Accuracy: 0.7976 - F1: 0.7976
sub_12:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8333 - F1: 0.8325
sub_12:Test (Best Model) - Loss: 0.5024 - Accuracy: 0.7381 - F1: 0.7375
sub_12:Test (Best Model) - Loss: 0.5726 - Accuracy: 0.7143 - F1: 0.7005
sub_12:Test (Best Model) - Loss: 0.5302 - Accuracy: 0.7024 - F1: 0.6897
sub_12:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.7500 - F1: 0.7418
sub_12:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.7738 - F1: 0.7699
sub_12:Test (Best Model) - Loss: 0.5642 - Accuracy: 0.7024 - F1: 0.6897
sub_12:Test (Best Model) - Loss: 0.5979 - Accuracy: 0.6190 - F1: 0.5787
sub_12:Test (Best Model) - Loss: 0.5925 - Accuracy: 0.6190 - F1: 0.6082
sub_12:Test (Best Model) - Loss: 0.5588 - Accuracy: 0.7024 - F1: 0.6926
sub_12:Test (Best Model) - Loss: 0.5771 - Accuracy: 0.6786 - F1: 0.6730
sub_12:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.6429 - F1: 0.6294
sub_13:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.7143 - F1: 0.7141
sub_13:Test (Best Model) - Loss: 0.6236 - Accuracy: 0.6786 - F1: 0.6774
sub_13:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.5443 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 0.5634 - Accuracy: 0.7500 - F1: 0.7500
sub_13:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.6429 - F1: 0.6354
sub_13:Test (Best Model) - Loss: 0.5472 - Accuracy: 0.6786 - F1: 0.6748
sub_13:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.6429 - F1: 0.6354
sub_13:Test (Best Model) - Loss: 0.5593 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 0.5458 - Accuracy: 0.7619 - F1: 0.7614
sub_13:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.7262 - F1: 0.7258
sub_13:Test (Best Model) - Loss: 0.5840 - Accuracy: 0.6905 - F1: 0.6876
sub_13:Test (Best Model) - Loss: 0.5603 - Accuracy: 0.7976 - F1: 0.7974
sub_13:Test (Best Model) - Loss: 0.5484 - Accuracy: 0.7857 - F1: 0.7856
sub_14:Test (Best Model) - Loss: 0.5822 - Accuracy: 0.7024 - F1: 0.7020
sub_14:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.7381 - F1: 0.7368
sub_14:Test (Best Model) - Loss: 0.5204 - Accuracy: 0.7262 - F1: 0.7243
sub_14:Test (Best Model) - Loss: 0.5349 - Accuracy: 0.7619 - F1: 0.7619
sub_14:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.7262 - F1: 0.7258
sub_14:Test (Best Model) - Loss: 0.5113 - Accuracy: 0.7738 - F1: 0.7712
sub_14:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.6429 - F1: 0.6327
sub_14:Test (Best Model) - Loss: 0.5436 - Accuracy: 0.7143 - F1: 0.7102
sub_14:Test (Best Model) - Loss: 0.5032 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 0.5088 - Accuracy: 0.7381 - F1: 0.7326
sub_14:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.6667 - F1: 0.6665
sub_14:Test (Best Model) - Loss: 0.5721 - Accuracy: 0.7262 - F1: 0.7262
sub_14:Test (Best Model) - Loss: 0.5691 - Accuracy: 0.7381 - F1: 0.7381
sub_14:Test (Best Model) - Loss: 0.5922 - Accuracy: 0.7262 - F1: 0.7262
sub_14:Test (Best Model) - Loss: 0.5855 - Accuracy: 0.7381 - F1: 0.7381

=== Summary Results ===

acc: 68.56 ± 6.45
F1: 67.80 ± 6.60
acc-in: 73.85 ± 7.04
F1-in: 73.27 ± 7.36
