lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.6786 - F1: 0.6680
sub_1:Test (Best Model) - Loss: 0.9438 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.6905 - F1: 0.6677
sub_1:Test (Best Model) - Loss: 0.7885 - Accuracy: 0.6905 - F1: 0.6719
sub_1:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.7143 - F1: 0.7005
sub_1:Test (Best Model) - Loss: 0.9163 - Accuracy: 0.6310 - F1: 0.6305
sub_1:Test (Best Model) - Loss: 0.8569 - Accuracy: 0.5952 - F1: 0.5932
sub_1:Test (Best Model) - Loss: 0.7974 - Accuracy: 0.7619 - F1: 0.7618
sub_1:Test (Best Model) - Loss: 0.8026 - Accuracy: 0.7143 - F1: 0.7141
sub_1:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.7500 - F1: 0.7500
sub_1:Test (Best Model) - Loss: 0.8476 - Accuracy: 0.7381 - F1: 0.7224
sub_1:Test (Best Model) - Loss: 0.8515 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.7306 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 0.7507 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.8462 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.7561 - Accuracy: 0.6786 - F1: 0.6730
sub_2:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.6190 - F1: 0.6136
sub_2:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.7024 - F1: 0.7003
sub_2:Test (Best Model) - Loss: 0.7611 - Accuracy: 0.6071 - F1: 0.5942
sub_2:Test (Best Model) - Loss: 0.7627 - Accuracy: 0.5952 - F1: 0.5868
sub_2:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.6905 - F1: 0.6860
sub_2:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.6548 - F1: 0.6535
sub_2:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.7619 - F1: 0.7618
sub_2:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.6667 - F1: 0.6636
sub_2:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.7143 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.9101 - Accuracy: 0.6548 - F1: 0.6508
sub_2:Test (Best Model) - Loss: 0.9475 - Accuracy: 0.6310 - F1: 0.6284
sub_2:Test (Best Model) - Loss: 1.0047 - Accuracy: 0.6548 - F1: 0.6487
sub_2:Test (Best Model) - Loss: 0.7334 - Accuracy: 0.6667 - F1: 0.6597
sub_2:Test (Best Model) - Loss: 0.9049 - Accuracy: 0.6786 - F1: 0.6763
sub_3:Test (Best Model) - Loss: 1.0717 - Accuracy: 0.5833 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 0.9249 - Accuracy: 0.6071 - F1: 0.5860
sub_3:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.6071 - F1: 0.5942
sub_3:Test (Best Model) - Loss: 0.9293 - Accuracy: 0.6190 - F1: 0.6007
sub_3:Test (Best Model) - Loss: 0.8637 - Accuracy: 0.5833 - F1: 0.5353
sub_3:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.6071 - F1: 0.6071
sub_3:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6548 - F1: 0.6535
sub_3:Test (Best Model) - Loss: 0.8385 - Accuracy: 0.5952 - F1: 0.5950
sub_3:Test (Best Model) - Loss: 0.7571 - Accuracy: 0.7381 - F1: 0.7375
sub_3:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.6548 - F1: 0.6543
sub_3:Test (Best Model) - Loss: 0.8772 - Accuracy: 0.6786 - F1: 0.6571
sub_3:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.6786 - F1: 0.6525
sub_3:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.6071 - F1: 0.5942
sub_3:Test (Best Model) - Loss: 0.7685 - Accuracy: 0.6071 - F1: 0.6003
sub_3:Test (Best Model) - Loss: 0.9328 - Accuracy: 0.6905 - F1: 0.6630
sub_4:Test (Best Model) - Loss: 1.1023 - Accuracy: 0.5595 - F1: 0.5595
sub_4:Test (Best Model) - Loss: 1.1829 - Accuracy: 0.4762 - F1: 0.4759
sub_4:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.5238 - F1: 0.5195
sub_4:Test (Best Model) - Loss: 1.2930 - Accuracy: 0.5476 - F1: 0.5435
sub_4:Test (Best Model) - Loss: 1.0731 - Accuracy: 0.5476 - F1: 0.5453
sub_4:Test (Best Model) - Loss: 0.9746 - Accuracy: 0.5833 - F1: 0.5785
sub_4:Test (Best Model) - Loss: 0.8663 - Accuracy: 0.6310 - F1: 0.6284
sub_4:Test (Best Model) - Loss: 0.8353 - Accuracy: 0.5952 - F1: 0.5943
sub_4:Test (Best Model) - Loss: 0.7933 - Accuracy: 0.5595 - F1: 0.5590
sub_4:Test (Best Model) - Loss: 0.8313 - Accuracy: 0.5476 - F1: 0.5453
sub_4:Test (Best Model) - Loss: 0.8602 - Accuracy: 0.5238 - F1: 0.5227
sub_4:Test (Best Model) - Loss: 1.0032 - Accuracy: 0.6071 - F1: 0.6066
sub_4:Test (Best Model) - Loss: 0.8194 - Accuracy: 0.6190 - F1: 0.6188
sub_4:Test (Best Model) - Loss: 1.1112 - Accuracy: 0.6071 - F1: 0.6044
sub_4:Test (Best Model) - Loss: 1.0383 - Accuracy: 0.5000 - F1: 0.4989
sub_5:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.7024 - F1: 0.7020
sub_5:Test (Best Model) - Loss: 0.7871 - Accuracy: 0.5714 - F1: 0.5705
sub_5:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.6548 - F1: 0.6523
sub_5:Test (Best Model) - Loss: 0.8483 - Accuracy: 0.6190 - F1: 0.6136
sub_5:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.7381 - F1: 0.7379
sub_5:Test (Best Model) - Loss: 0.7479 - Accuracy: 0.6667 - F1: 0.6636
sub_5:Test (Best Model) - Loss: 0.8487 - Accuracy: 0.6190 - F1: 0.6156
sub_5:Test (Best Model) - Loss: 0.7523 - Accuracy: 0.6071 - F1: 0.6066
sub_5:Test (Best Model) - Loss: 0.7341 - Accuracy: 0.6429 - F1: 0.6420
sub_5:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.5833 - F1: 0.5785
sub_5:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.6786 - F1: 0.6748
sub_5:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7024 - F1: 0.7020
sub_5:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.7143 - F1: 0.7141
sub_5:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.7619 - F1: 0.7607
sub_5:Test (Best Model) - Loss: 0.7498 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 1.4454 - Accuracy: 0.5357 - F1: 0.5325
sub_6:Test (Best Model) - Loss: 1.1931 - Accuracy: 0.5238 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 1.1957 - Accuracy: 0.5595 - F1: 0.5580
sub_6:Test (Best Model) - Loss: 1.0966 - Accuracy: 0.5476 - F1: 0.5476
sub_6:Test (Best Model) - Loss: 1.0651 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 1.1075 - Accuracy: 0.6429 - F1: 0.6410
sub_6:Test (Best Model) - Loss: 1.1724 - Accuracy: 0.5714 - F1: 0.5675
sub_6:Test (Best Model) - Loss: 0.9218 - Accuracy: 0.5952 - F1: 0.5950
sub_6:Test (Best Model) - Loss: 1.1684 - Accuracy: 0.5357 - F1: 0.5341
sub_6:Test (Best Model) - Loss: 0.7691 - Accuracy: 0.5595 - F1: 0.5590
sub_6:Test (Best Model) - Loss: 0.9437 - Accuracy: 0.6667 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 1.0222 - Accuracy: 0.5238 - F1: 0.5238
sub_6:Test (Best Model) - Loss: 0.7485 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 1.1642 - Accuracy: 0.5238 - F1: 0.5235
sub_6:Test (Best Model) - Loss: 0.9616 - Accuracy: 0.5357 - F1: 0.5351
sub_7:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.5952 - F1: 0.5943
sub_7:Test (Best Model) - Loss: 0.8581 - Accuracy: 0.4762 - F1: 0.4714
sub_7:Test (Best Model) - Loss: 0.9307 - Accuracy: 0.6786 - F1: 0.6774
sub_7:Test (Best Model) - Loss: 0.9031 - Accuracy: 0.5476 - F1: 0.5474
sub_7:Test (Best Model) - Loss: 0.8103 - Accuracy: 0.6667 - F1: 0.6667
sub_7:Test (Best Model) - Loss: 1.0053 - Accuracy: 0.5000 - F1: 0.4974
sub_7:Test (Best Model) - Loss: 0.8325 - Accuracy: 0.5714 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 0.9484 - Accuracy: 0.5000 - F1: 0.4928
sub_7:Test (Best Model) - Loss: 1.0815 - Accuracy: 0.5357 - F1: 0.5341
sub_7:Test (Best Model) - Loss: 0.8089 - Accuracy: 0.5595 - F1: 0.5487
sub_7:Test (Best Model) - Loss: 0.9093 - Accuracy: 0.5714 - F1: 0.5705
sub_7:Test (Best Model) - Loss: 0.9588 - Accuracy: 0.5119 - F1: 0.5118
sub_7:Test (Best Model) - Loss: 0.7307 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 0.9058 - Accuracy: 0.5238 - F1: 0.5235
sub_7:Test (Best Model) - Loss: 0.9263 - Accuracy: 0.5476 - F1: 0.5435
sub_8:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.5360 - Accuracy: 0.7143 - F1: 0.7143
sub_8:Test (Best Model) - Loss: 0.5601 - Accuracy: 0.7738 - F1: 0.7722
sub_8:Test (Best Model) - Loss: 0.5381 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.5254 - Accuracy: 0.7262 - F1: 0.7258
sub_8:Test (Best Model) - Loss: 0.7286 - Accuracy: 0.6786 - F1: 0.6748
sub_8:Test (Best Model) - Loss: 0.7369 - Accuracy: 0.6786 - F1: 0.6782
sub_8:Test (Best Model) - Loss: 0.7644 - Accuracy: 0.6429 - F1: 0.6377
sub_8:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.6786 - F1: 0.6785
sub_8:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.6786 - F1: 0.6763
sub_8:Test (Best Model) - Loss: 0.5589 - Accuracy: 0.7857 - F1: 0.7852
sub_8:Test (Best Model) - Loss: 0.5294 - Accuracy: 0.7262 - F1: 0.7252
sub_8:Test (Best Model) - Loss: 0.5466 - Accuracy: 0.7143 - F1: 0.7102
sub_8:Test (Best Model) - Loss: 0.4272 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.6786 - F1: 0.6785
sub_9:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6905 - F1: 0.6876
sub_9:Test (Best Model) - Loss: 0.8358 - Accuracy: 0.6310 - F1: 0.6305
sub_9:Test (Best Model) - Loss: 0.5791 - Accuracy: 0.7262 - F1: 0.7230
sub_9:Test (Best Model) - Loss: 0.7391 - Accuracy: 0.6905 - F1: 0.6898
sub_9:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6905 - F1: 0.6898
sub_9:Test (Best Model) - Loss: 0.7493 - Accuracy: 0.6905 - F1: 0.6860
sub_9:Test (Best Model) - Loss: 0.8481 - Accuracy: 0.6310 - F1: 0.6284
sub_9:Test (Best Model) - Loss: 1.1579 - Accuracy: 0.5833 - F1: 0.5819
sub_9:Test (Best Model) - Loss: 0.8356 - Accuracy: 0.6310 - F1: 0.6296
sub_9:Test (Best Model) - Loss: 0.8818 - Accuracy: 0.6310 - F1: 0.6296
sub_9:Test (Best Model) - Loss: 0.9135 - Accuracy: 0.6190 - F1: 0.5910
sub_9:Test (Best Model) - Loss: 0.8002 - Accuracy: 0.6667 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.6786 - F1: 0.6707
sub_9:Test (Best Model) - Loss: 0.6510 - Accuracy: 0.6310 - F1: 0.6305
sub_9:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.6905 - F1: 0.6719
sub_10:Test (Best Model) - Loss: 0.8154 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 0.8942 - Accuracy: 0.6190 - F1: 0.6136
sub_10:Test (Best Model) - Loss: 0.8254 - Accuracy: 0.6310 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.8646 - Accuracy: 0.5952 - F1: 0.5915
sub_10:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.5595 - F1: 0.5595
sub_10:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.5833 - F1: 0.5828
sub_10:Test (Best Model) - Loss: 0.8003 - Accuracy: 0.5833 - F1: 0.5828
sub_10:Test (Best Model) - Loss: 0.8985 - Accuracy: 0.5833 - F1: 0.5833
sub_10:Test (Best Model) - Loss: 0.7849 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 0.7981 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.8127 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 0.7508 - Accuracy: 0.6667 - F1: 0.6636
sub_10:Test (Best Model) - Loss: 1.0380 - Accuracy: 0.7024 - F1: 0.6897
sub_10:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.6905 - F1: 0.6905
sub_11:Test (Best Model) - Loss: 1.1061 - Accuracy: 0.4762 - F1: 0.4759
sub_11:Test (Best Model) - Loss: 1.0723 - Accuracy: 0.5476 - F1: 0.5466
sub_11:Test (Best Model) - Loss: 0.9456 - Accuracy: 0.5119 - F1: 0.5113
sub_11:Test (Best Model) - Loss: 1.0500 - Accuracy: 0.4524 - F1: 0.4511
sub_11:Test (Best Model) - Loss: 0.8197 - Accuracy: 0.5714 - F1: 0.5712
sub_11:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6310 - F1: 0.6309
sub_11:Test (Best Model) - Loss: 0.9056 - Accuracy: 0.6429 - F1: 0.6420
sub_11:Test (Best Model) - Loss: 0.7991 - Accuracy: 0.5833 - F1: 0.5804
sub_11:Test (Best Model) - Loss: 0.8479 - Accuracy: 0.5714 - F1: 0.5705
sub_11:Test (Best Model) - Loss: 0.8465 - Accuracy: 0.6190 - F1: 0.6171
sub_11:Test (Best Model) - Loss: 0.9876 - Accuracy: 0.6429 - F1: 0.6427
sub_11:Test (Best Model) - Loss: 1.0979 - Accuracy: 0.5952 - F1: 0.5932
sub_11:Test (Best Model) - Loss: 0.9426 - Accuracy: 0.6190 - F1: 0.6182
sub_11:Test (Best Model) - Loss: 0.8418 - Accuracy: 0.5833 - F1: 0.5804
sub_11:Test (Best Model) - Loss: 0.8101 - Accuracy: 0.6190 - F1: 0.6188
sub_12:Test (Best Model) - Loss: 1.0026 - Accuracy: 0.6190 - F1: 0.6188
sub_12:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.7024 - F1: 0.7013
sub_12:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6667 - F1: 0.6659
sub_12:Test (Best Model) - Loss: 0.5830 - Accuracy: 0.7143 - F1: 0.7128
sub_12:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.7381 - F1: 0.7379
sub_12:Test (Best Model) - Loss: 1.0809 - Accuracy: 0.6905 - F1: 0.6756
sub_12:Test (Best Model) - Loss: 0.8942 - Accuracy: 0.5833 - F1: 0.5655
sub_12:Test (Best Model) - Loss: 1.0745 - Accuracy: 0.6667 - F1: 0.6421
sub_12:Test (Best Model) - Loss: 0.8678 - Accuracy: 0.7024 - F1: 0.6897
sub_12:Test (Best Model) - Loss: 0.9493 - Accuracy: 0.6429 - F1: 0.6257
sub_12:Test (Best Model) - Loss: 0.8412 - Accuracy: 0.5714 - F1: 0.5625
sub_12:Test (Best Model) - Loss: 0.9129 - Accuracy: 0.6548 - F1: 0.6523
sub_12:Test (Best Model) - Loss: 0.7969 - Accuracy: 0.6310 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 0.7563 - Accuracy: 0.6310 - F1: 0.6284
sub_12:Test (Best Model) - Loss: 1.1401 - Accuracy: 0.5952 - F1: 0.5837
sub_13:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.6786 - F1: 0.6748
sub_13:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.7143 - F1: 0.7061
sub_13:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.7820 - Accuracy: 0.6667 - F1: 0.6597
sub_13:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.6786 - F1: 0.6748
sub_13:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.6905 - F1: 0.6860
sub_13:Test (Best Model) - Loss: 0.5115 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 0.4894 - Accuracy: 0.7500 - F1: 0.7491
sub_13:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.7024 - F1: 0.7003
sub_13:Test (Best Model) - Loss: 0.5442 - Accuracy: 0.7976 - F1: 0.7969
sub_13:Test (Best Model) - Loss: 0.5455 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.6222 - Accuracy: 0.7024 - F1: 0.6989
sub_14:Test (Best Model) - Loss: 0.8236 - Accuracy: 0.7024 - F1: 0.7013
sub_14:Test (Best Model) - Loss: 0.9590 - Accuracy: 0.5952 - F1: 0.5950
sub_14:Test (Best Model) - Loss: 0.7185 - Accuracy: 0.6786 - F1: 0.6782
sub_14:Test (Best Model) - Loss: 0.9346 - Accuracy: 0.7143 - F1: 0.7141
sub_14:Test (Best Model) - Loss: 1.0747 - Accuracy: 0.5952 - F1: 0.5932
sub_14:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.7381 - F1: 0.7375
sub_14:Test (Best Model) - Loss: 0.9561 - Accuracy: 0.5595 - F1: 0.5487
sub_14:Test (Best Model) - Loss: 0.8187 - Accuracy: 0.6071 - F1: 0.6003
sub_14:Test (Best Model) - Loss: 0.7772 - Accuracy: 0.6310 - F1: 0.6305
sub_14:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.7024 - F1: 0.7003
sub_14:Test (Best Model) - Loss: 0.8766 - Accuracy: 0.5952 - F1: 0.5868
sub_14:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.7143 - F1: 0.7128
sub_14:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.6667 - F1: 0.6619
sub_14:Test (Best Model) - Loss: 0.7719 - Accuracy: 0.6310 - F1: 0.6309
sub_14:Test (Best Model) - Loss: 0.7752 - Accuracy: 0.6071 - F1: 0.6044

=== Summary Results ===

acc: 63.93 ± 5.46
F1: 63.46 ± 5.35
acc-in: 69.14 ± 5.90
F1-in: 68.85 ± 5.97
