lr: 0.001
sub_13:Test (Best Model) - Loss: 0.2152 - Accuracy: 0.9286 - F1: 0.9285
sub_4:Test (Best Model) - Loss: 0.3481 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 1.0601 - Accuracy: 0.6190 - F1: 0.5852
sub_12:Test (Best Model) - Loss: 0.2853 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.3867 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.1860 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.1644 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.5612 - Accuracy: 0.7976 - F1: 0.7890
sub_7:Test (Best Model) - Loss: 1.2341 - Accuracy: 0.6190 - F1: 0.5634
sub_5:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.7500 - F1: 0.7471
sub_10:Test (Best Model) - Loss: 0.3128 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.3103 - Accuracy: 0.8929 - F1: 0.8925
sub_1:Test (Best Model) - Loss: 0.1964 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.3214 - Accuracy: 0.8810 - F1: 0.8799
sub_13:Test (Best Model) - Loss: 0.1942 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.2447 - Accuracy: 0.9167 - F1: 0.9161
sub_12:Test (Best Model) - Loss: 0.2962 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 1.1894 - Accuracy: 0.6429 - F1: 0.6257
sub_6:Test (Best Model) - Loss: 0.2557 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.4145 - Accuracy: 0.8571 - F1: 0.8551
sub_4:Test (Best Model) - Loss: 0.7343 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.2489 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.3810 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.8214 - F1: 0.8170
sub_13:Test (Best Model) - Loss: 0.3548 - Accuracy: 0.8690 - F1: 0.8686
sub_7:Test (Best Model) - Loss: 1.0156 - Accuracy: 0.7381 - F1: 0.7188
sub_6:Test (Best Model) - Loss: 0.3602 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.0503 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.7733 - Accuracy: 0.7024 - F1: 0.6897
sub_12:Test (Best Model) - Loss: 0.1826 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.2153 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.2805 - Accuracy: 0.9167 - F1: 0.9161
sub_4:Test (Best Model) - Loss: 0.5202 - Accuracy: 0.8095 - F1: 0.8041
sub_5:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.7619 - F1: 0.7618
sub_8:Test (Best Model) - Loss: 0.1681 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.1949 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.7705 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 0.1681 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.4838 - Accuracy: 0.8452 - F1: 0.8425
sub_12:Test (Best Model) - Loss: 0.4000 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.2104 - Accuracy: 0.9405 - F1: 0.9403
sub_6:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.1644 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.2492 - Accuracy: 0.9405 - F1: 0.9404
sub_14:Test (Best Model) - Loss: 0.9450 - Accuracy: 0.6786 - F1: 0.6415
sub_8:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.9023 - Accuracy: 0.7024 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.2276 - Accuracy: 0.9286 - F1: 0.9285
sub_3:Test (Best Model) - Loss: 0.3381 - Accuracy: 0.8690 - F1: 0.8675
sub_10:Test (Best Model) - Loss: 0.2947 - Accuracy: 0.9048 - F1: 0.9047
sub_12:Test (Best Model) - Loss: 0.4749 - Accuracy: 0.8214 - F1: 0.8155
sub_7:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.7619 - F1: 0.7476
sub_4:Test (Best Model) - Loss: 0.4982 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.1507 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.2095 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.3159 - Accuracy: 0.8571 - F1: 0.8542
sub_5:Test (Best Model) - Loss: 0.8147 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 0.5724 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 0.2218 - Accuracy: 0.9286 - F1: 0.9285
sub_11:Test (Best Model) - Loss: 0.2094 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.3523 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.0625 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.2141 - Accuracy: 0.9286 - F1: 0.9285
sub_14:Test (Best Model) - Loss: 0.7381 - Accuracy: 0.7500 - F1: 0.7439
sub_13:Test (Best Model) - Loss: 0.2157 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.4146 - Accuracy: 0.8690 - F1: 0.8681
sub_11:Test (Best Model) - Loss: 0.2569 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.1321 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.5535 - Accuracy: 0.8333 - F1: 0.8299
sub_7:Test (Best Model) - Loss: 0.9247 - Accuracy: 0.7143 - F1: 0.6889
sub_5:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.7500 - F1: 0.7491
sub_2:Test (Best Model) - Loss: 0.5114 - Accuracy: 0.8571 - F1: 0.8551
sub_3:Test (Best Model) - Loss: 0.4176 - Accuracy: 0.8571 - F1: 0.8558
sub_9:Test (Best Model) - Loss: 0.2171 - Accuracy: 0.9286 - F1: 0.9284
sub_12:Test (Best Model) - Loss: 0.2711 - Accuracy: 0.8929 - F1: 0.8927
sub_1:Test (Best Model) - Loss: 0.3488 - Accuracy: 0.8929 - F1: 0.8925
sub_6:Test (Best Model) - Loss: 0.4156 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.1116 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.2552 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.8095 - F1: 0.8024
sub_13:Test (Best Model) - Loss: 0.2406 - Accuracy: 0.9167 - F1: 0.9166
sub_2:Test (Best Model) - Loss: 0.2024 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.1250 - Accuracy: 0.9524 - F1: 0.9524
sub_5:Test (Best Model) - Loss: 0.2341 - Accuracy: 0.9048 - F1: 0.9047
sub_9:Test (Best Model) - Loss: 0.4865 - Accuracy: 0.8095 - F1: 0.8024
sub_7:Test (Best Model) - Loss: 0.2389 - Accuracy: 0.9286 - F1: 0.9285
sub_3:Test (Best Model) - Loss: 0.2313 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.4323 - Accuracy: 0.8452 - F1: 0.8447
sub_6:Test (Best Model) - Loss: 0.1616 - Accuracy: 0.9286 - F1: 0.9284
sub_13:Test (Best Model) - Loss: 0.2771 - Accuracy: 0.9048 - F1: 0.9048
sub_1:Test (Best Model) - Loss: 0.5262 - Accuracy: 0.8214 - F1: 0.8155
sub_11:Test (Best Model) - Loss: 0.1873 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.2762 - Accuracy: 0.9286 - F1: 0.9286
sub_14:Test (Best Model) - Loss: 0.1756 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.1879 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.3267 - Accuracy: 0.8929 - F1: 0.8928
sub_2:Test (Best Model) - Loss: 0.4184 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 0.3354 - Accuracy: 0.8929 - F1: 0.8927
sub_6:Test (Best Model) - Loss: 0.3008 - Accuracy: 0.9048 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.1980 - Accuracy: 0.9167 - F1: 0.9164
sub_13:Test (Best Model) - Loss: 0.1895 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.1903 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.8333 - F1: 0.8309
sub_3:Test (Best Model) - Loss: 0.1537 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.3757 - Accuracy: 0.8810 - F1: 0.8810
sub_5:Test (Best Model) - Loss: 0.3020 - Accuracy: 0.8929 - F1: 0.8928
sub_8:Test (Best Model) - Loss: 0.1276 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.2073 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.6905 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 0.2380 - Accuracy: 0.9167 - F1: 0.9164
sub_13:Test (Best Model) - Loss: 0.2105 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.5150 - Accuracy: 0.8214 - F1: 0.8155
sub_1:Test (Best Model) - Loss: 0.3219 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.2030 - Accuracy: 0.9286 - F1: 0.9286
sub_5:Test (Best Model) - Loss: 0.5963 - Accuracy: 0.8095 - F1: 0.8068
sub_12:Test (Best Model) - Loss: 0.5303 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 0.3550 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 0.2970 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.1404 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.1666 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.1456 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.5884 - Accuracy: 0.7619 - F1: 0.7607
sub_3:Test (Best Model) - Loss: 0.3755 - Accuracy: 0.8810 - F1: 0.8799
sub_4:Test (Best Model) - Loss: 0.3861 - Accuracy: 0.8690 - F1: 0.8686
sub_2:Test (Best Model) - Loss: 0.5989 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.8333 - F1: 0.8299
sub_8:Test (Best Model) - Loss: 0.2383 - Accuracy: 0.9167 - F1: 0.9164
sub_1:Test (Best Model) - Loss: 0.3554 - Accuracy: 0.8929 - F1: 0.8916
sub_5:Test (Best Model) - Loss: 0.1978 - Accuracy: 0.9405 - F1: 0.9404
sub_14:Test (Best Model) - Loss: 0.4161 - Accuracy: 0.8571 - F1: 0.8542
sub_6:Test (Best Model) - Loss: 0.2716 - Accuracy: 0.9167 - F1: 0.9166
sub_11:Test (Best Model) - Loss: 0.1589 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.3685 - Accuracy: 0.8810 - F1: 0.8810
sub_4:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.3736 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.3533 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 0.3085 - Accuracy: 0.8929 - F1: 0.8927
sub_3:Test (Best Model) - Loss: 0.3236 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.3396 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.2891 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 0.1787 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.2402 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.4768 - Accuracy: 0.8214 - F1: 0.8194
sub_5:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.8810 - F1: 0.8799
sub_11:Test (Best Model) - Loss: 0.2640 - Accuracy: 0.8810 - F1: 0.8809
sub_4:Test (Best Model) - Loss: 0.4623 - Accuracy: 0.8095 - F1: 0.8078
sub_7:Test (Best Model) - Loss: 0.3165 - Accuracy: 0.8929 - F1: 0.8927
sub_3:Test (Best Model) - Loss: 0.2618 - Accuracy: 0.9167 - F1: 0.9167
sub_2:Test (Best Model) - Loss: 0.2666 - Accuracy: 0.9048 - F1: 0.9043
sub_9:Test (Best Model) - Loss: 0.5105 - Accuracy: 0.8095 - F1: 0.8068
sub_1:Test (Best Model) - Loss: 0.0728 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.1782 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.3403 - Accuracy: 0.9048 - F1: 0.9047
sub_10:Test (Best Model) - Loss: 0.4270 - Accuracy: 0.8214 - F1: 0.8170
sub_8:Test (Best Model) - Loss: 0.1973 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 1.2332 - Accuracy: 0.5714 - F1: 0.4750
sub_5:Test (Best Model) - Loss: 0.7989 - Accuracy: 0.7024 - F1: 0.6897
sub_6:Test (Best Model) - Loss: 0.5151 - Accuracy: 0.8333 - F1: 0.8325
sub_3:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.7976 - F1: 0.7927
sub_11:Test (Best Model) - Loss: 0.3774 - Accuracy: 0.8690 - F1: 0.8689
sub_13:Test (Best Model) - Loss: 0.0925 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.4394 - Accuracy: 0.8452 - F1: 0.8425
sub_12:Test (Best Model) - Loss: 0.3880 - Accuracy: 0.8690 - F1: 0.8681
sub_7:Test (Best Model) - Loss: 0.9159 - Accuracy: 0.7381 - F1: 0.7255
sub_10:Test (Best Model) - Loss: 0.7984 - Accuracy: 0.7500 - F1: 0.7365
sub_2:Test (Best Model) - Loss: 0.4659 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7619 - F1: 0.7529
sub_1:Test (Best Model) - Loss: 0.2266 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.1762 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.1588 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.4112 - Accuracy: 0.8333 - F1: 0.8309
sub_4:Test (Best Model) - Loss: 0.8764 - Accuracy: 0.7024 - F1: 0.6735
sub_12:Test (Best Model) - Loss: 0.3999 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 1.4575 - Accuracy: 0.6310 - F1: 0.5728
sub_3:Test (Best Model) - Loss: 0.4325 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 0.2823 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.5250 - Accuracy: 0.8333 - F1: 0.8330
sub_10:Test (Best Model) - Loss: 1.2128 - Accuracy: 0.6190 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 0.4906 - Accuracy: 0.8095 - F1: 0.8094
sub_2:Test (Best Model) - Loss: 0.5370 - Accuracy: 0.8333 - F1: 0.8299
sub_1:Test (Best Model) - Loss: 0.2028 - Accuracy: 0.9286 - F1: 0.9286
sub_9:Test (Best Model) - Loss: 0.3203 - Accuracy: 0.8929 - F1: 0.8916
sub_5:Test (Best Model) - Loss: 0.9368 - Accuracy: 0.7024 - F1: 0.6735
sub_14:Test (Best Model) - Loss: 1.4423 - Accuracy: 0.5238 - F1: 0.3842
sub_4:Test (Best Model) - Loss: 0.5089 - Accuracy: 0.7738 - F1: 0.7641
sub_2:Test (Best Model) - Loss: 0.3073 - Accuracy: 0.8690 - F1: 0.8675
sub_9:Test (Best Model) - Loss: 0.4027 - Accuracy: 0.8452 - F1: 0.8425
sub_6:Test (Best Model) - Loss: 0.5469 - Accuracy: 0.8214 - F1: 0.8155
sub_10:Test (Best Model) - Loss: 0.3657 - Accuracy: 0.8690 - F1: 0.8689
sub_3:Test (Best Model) - Loss: 0.3975 - Accuracy: 0.8214 - F1: 0.8155
sub_1:Test (Best Model) - Loss: 0.2283 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 1.0621 - Accuracy: 0.5833 - F1: 0.4958
sub_5:Test (Best Model) - Loss: 0.8756 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.3638 - Accuracy: 0.8571 - F1: 0.8551
sub_7:Test (Best Model) - Loss: 0.5665 - Accuracy: 0.7857 - F1: 0.7846
sub_10:Test (Best Model) - Loss: 0.3478 - Accuracy: 0.8810 - F1: 0.8807
sub_6:Test (Best Model) - Loss: 0.4408 - Accuracy: 0.8214 - F1: 0.8208
sub_4:Test (Best Model) - Loss: 0.8679 - Accuracy: 0.7381 - F1: 0.7188
sub_3:Test (Best Model) - Loss: 0.4367 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.2670 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 1.5625 - Accuracy: 0.5119 - F1: 0.3778
sub_7:Test (Best Model) - Loss: 0.3671 - Accuracy: 0.8690 - F1: 0.8689
sub_3:Test (Best Model) - Loss: 0.4853 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 0.4407 - Accuracy: 0.8452 - F1: 0.8434
sub_4:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.7738 - F1: 0.7664
sub_7:Test (Best Model) - Loss: 0.3046 - Accuracy: 0.9048 - F1: 0.9043
sub_4:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.7619 - F1: 0.7476

=== Summary Results ===

acc: 86.09 ± 6.23
F1: 85.49 ± 7.12
acc-in: 95.96 ± 1.97
F1-in: 95.93 ± 1.99
