lr: 1e-05
sub_7:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6548 - F1: 0.6543
sub_10:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.5952 - F1: 0.5159
sub_14:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.7500 - F1: 0.7333
sub_11:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.8690 - F1: 0.8675
sub_4:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.5914 - Accuracy: 0.7500 - F1: 0.7393
sub_1:Test (Best Model) - Loss: 0.6079 - Accuracy: 0.7619 - F1: 0.7504
sub_9:Test (Best Model) - Loss: 0.5378 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.6905 - F1: 0.6630
sub_3:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.7976 - F1: 0.7941
sub_12:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6190 - F1: 0.5544
sub_13:Test (Best Model) - Loss: 0.5920 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.6429 - F1: 0.6377
sub_11:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.8690 - F1: 0.8675
sub_8:Test (Best Model) - Loss: 0.5634 - Accuracy: 0.9405 - F1: 0.9405
sub_14:Test (Best Model) - Loss: 0.5811 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.5939 - Accuracy: 0.9405 - F1: 0.9404
sub_1:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 0.5721 - Accuracy: 0.8333 - F1: 0.8286
sub_7:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.7619 - F1: 0.7607
sub_12:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.5997 - Accuracy: 0.8452 - F1: 0.8442
sub_9:Test (Best Model) - Loss: 0.5717 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.5286 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.8095 - F1: 0.8041
sub_13:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.7738 - F1: 0.7641
sub_6:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.6548 - F1: 0.6212
sub_3:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.9048 - F1: 0.9047
sub_11:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.8452 - F1: 0.8425
sub_4:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.9286 - F1: 0.9284
sub_1:Test (Best Model) - Loss: 0.5862 - Accuracy: 0.8929 - F1: 0.8921
sub_5:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.7619 - F1: 0.7619
sub_14:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.8095 - F1: 0.8041
sub_7:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.7262 - F1: 0.7195
sub_12:Test (Best Model) - Loss: 0.5144 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.5803 - Accuracy: 0.9167 - F1: 0.9167
sub_13:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.8333 - F1: 0.8309
sub_10:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.8333 - F1: 0.8309
sub_11:Test (Best Model) - Loss: 0.6170 - Accuracy: 0.8452 - F1: 0.8434
sub_4:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.6071 - F1: 0.5452
sub_9:Test (Best Model) - Loss: 0.6309 - Accuracy: 0.8690 - F1: 0.8675
sub_6:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.7857 - F1: 0.7856
sub_5:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.6007 - Accuracy: 0.8214 - F1: 0.8170
sub_7:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5357 - F1: 0.5048
sub_3:Test (Best Model) - Loss: 0.6215 - Accuracy: 0.8571 - F1: 0.8568
sub_1:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.5375 - Accuracy: 0.9286 - F1: 0.9285
sub_10:Test (Best Model) - Loss: 0.5944 - Accuracy: 0.7143 - F1: 0.6932
sub_14:Test (Best Model) - Loss: 0.5812 - Accuracy: 0.8333 - F1: 0.8286
sub_11:Test (Best Model) - Loss: 0.5706 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.8929 - F1: 0.8928
sub_12:Test (Best Model) - Loss: 0.5709 - Accuracy: 0.8333 - F1: 0.8286
sub_13:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.8333 - F1: 0.8318
sub_9:Test (Best Model) - Loss: 0.5777 - Accuracy: 0.8810 - F1: 0.8799
sub_6:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.5569 - Accuracy: 0.8214 - F1: 0.8155
sub_8:Test (Best Model) - Loss: 0.5688 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.6012 - Accuracy: 0.7619 - F1: 0.7476
sub_5:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.7500 - F1: 0.7500
sub_1:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.8333 - F1: 0.8299
sub_10:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.9167 - F1: 0.9167
sub_7:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.6905 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.6310 - F1: 0.5728
sub_13:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.9167 - F1: 0.9166
sub_9:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.8571 - F1: 0.8542
sub_6:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.8095 - F1: 0.8041
sub_12:Test (Best Model) - Loss: 0.6025 - Accuracy: 0.8095 - F1: 0.8024
sub_11:Test (Best Model) - Loss: 0.5526 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.5515 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.5948 - Accuracy: 0.8333 - F1: 0.8330
sub_7:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.4762 - F1: 0.4107
sub_5:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.7857 - F1: 0.7838
sub_10:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.9167 - F1: 0.9166
sub_2:Test (Best Model) - Loss: 0.5365 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.5841 - Accuracy: 0.8929 - F1: 0.8921
sub_1:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.7262 - F1: 0.7114
sub_7:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7381 - F1: 0.7282
sub_4:Test (Best Model) - Loss: 0.5985 - Accuracy: 0.8571 - F1: 0.8571
sub_6:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.5821 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.7976 - F1: 0.7974
sub_13:Test (Best Model) - Loss: 0.5996 - Accuracy: 0.8929 - F1: 0.8921
sub_12:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.7738 - F1: 0.7616
sub_2:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.8333 - F1: 0.8286
sub_9:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 0.4820 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.8571 - F1: 0.8542
sub_3:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.7500 - F1: 0.7497
sub_14:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.5910 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.8452 - F1: 0.8434
sub_2:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.9167 - F1: 0.9164
sub_7:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.5952 - F1: 0.5265
sub_13:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.7857 - F1: 0.7796
sub_6:Test (Best Model) - Loss: 0.6100 - Accuracy: 0.8214 - F1: 0.8194
sub_11:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.5828 - Accuracy: 0.9167 - F1: 0.9167
sub_4:Test (Best Model) - Loss: 0.5487 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.5875 - Accuracy: 0.8452 - F1: 0.8442
sub_3:Test (Best Model) - Loss: 0.6212 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.5643 - Accuracy: 0.8929 - F1: 0.8927
sub_5:Test (Best Model) - Loss: 0.6014 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.5416 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.5927 - Accuracy: 0.7500 - F1: 0.7333
sub_7:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.7619 - F1: 0.7504
sub_4:Test (Best Model) - Loss: 0.6140 - Accuracy: 0.8095 - F1: 0.8024
sub_11:Test (Best Model) - Loss: 0.5569 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.5840 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.5605 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.6022 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.4881 - F1: 0.4822
sub_6:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7738 - F1: 0.7699
sub_12:Test (Best Model) - Loss: 0.6076 - Accuracy: 0.8690 - F1: 0.8668
sub_13:Test (Best Model) - Loss: 0.5768 - Accuracy: 0.8571 - F1: 0.8564
sub_10:Test (Best Model) - Loss: 0.5968 - Accuracy: 0.8929 - F1: 0.8927
sub_8:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.7738 - F1: 0.7616
sub_3:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.9167 - F1: 0.9166
sub_5:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.8095 - F1: 0.8094
sub_11:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5714 - F1: 0.5592
sub_4:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.9167 - F1: 0.9166
sub_9:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.7381 - F1: 0.7326
sub_14:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.7976 - F1: 0.7910
sub_1:Test (Best Model) - Loss: 0.5511 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.5568 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6786 - F1: 0.6525
sub_10:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.7262 - F1: 0.7040
sub_6:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.7619 - F1: 0.7614
sub_11:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5833 - F1: 0.5655
sub_8:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.8333 - F1: 0.8286
sub_4:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.9405 - F1: 0.9404
sub_13:Test (Best Model) - Loss: 0.6096 - Accuracy: 0.8690 - F1: 0.8681
sub_9:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.8929 - F1: 0.8927
sub_3:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6310 - F1: 0.6245
sub_2:Test (Best Model) - Loss: 0.6025 - Accuracy: 0.7857 - F1: 0.7776
sub_14:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.6190 - F1: 0.5714
sub_6:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.6310 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.7381 - F1: 0.7224
sub_10:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.6071 - F1: 0.5354
sub_5:Test (Best Model) - Loss: 0.6346 - Accuracy: 0.7738 - F1: 0.7735
sub_8:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.6136 - Accuracy: 0.8452 - F1: 0.8452
sub_4:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.7619 - F1: 0.7551
sub_1:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.7976 - F1: 0.7910
sub_14:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6310 - F1: 0.5951
sub_2:Test (Best Model) - Loss: 0.5939 - Accuracy: 0.8810 - F1: 0.8799
sub_13:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.8571 - F1: 0.8564
sub_7:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.5775 - Accuracy: 0.8929 - F1: 0.8921
sub_3:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.7024 - F1: 0.6735
sub_8:Test (Best Model) - Loss: 0.5079 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.7857 - F1: 0.7754
sub_6:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.6905 - F1: 0.6719
sub_9:Test (Best Model) - Loss: 0.6133 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.6097 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.8095 - F1: 0.8041
sub_14:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.6786 - F1: 0.6473
sub_11:Test (Best Model) - Loss: 0.5864 - Accuracy: 0.9405 - F1: 0.9404
sub_13:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.8214 - F1: 0.8170
sub_2:Test (Best Model) - Loss: 0.5057 - Accuracy: 0.9405 - F1: 0.9403
sub_6:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6667 - F1: 0.6313
sub_7:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.7500 - F1: 0.7483
sub_9:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.6429 - F1: 0.6050
sub_10:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.7262 - F1: 0.7145
sub_14:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.7262 - F1: 0.7258
sub_1:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.8690 - F1: 0.8686
sub_11:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.9405 - F1: 0.9405
sub_4:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.7381 - F1: 0.7188
sub_12:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.7381 - F1: 0.7188
sub_6:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.5833 - F1: 0.5073
sub_7:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.6429 - F1: 0.6427
sub_5:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.7738 - F1: 0.7722
sub_2:Test (Best Model) - Loss: 0.5684 - Accuracy: 0.8452 - F1: 0.8425
sub_10:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.5357 - F1: 0.4081
sub_13:Test (Best Model) - Loss: 0.5294 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.5595 - F1: 0.4791
sub_11:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.7619 - F1: 0.7618
sub_9:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.8571 - F1: 0.8558
sub_3:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5714 - F1: 0.4750
sub_5:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.7619 - F1: 0.7585
sub_6:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5595 - F1: 0.4535
sub_12:Test (Best Model) - Loss: 0.5743 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.8571 - F1: 0.8568
sub_1:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7619 - F1: 0.7551
sub_9:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.8571 - F1: 0.8564
sub_3:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6786 - F1: 0.6680
sub_12:Test (Best Model) - Loss: 0.5540 - Accuracy: 0.8929 - F1: 0.8921
sub_5:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5476 - F1: 0.4911
sub_3:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 0.5797 - Accuracy: 0.9167 - F1: 0.9167
sub_13:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.9048 - F1: 0.9043

=== Summary Results ===

acc: 81.23 ± 7.35
F1: 80.22 ± 8.08
acc-in: 88.64 ± 6.77
F1-in: 88.44 ± 7.09
