lr: 0.0001
sub_13:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.7619 - F1: 0.7476
sub_4:Test (Best Model) - Loss: 0.4522 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.3576 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 1.0126 - Accuracy: 0.8452 - F1: 0.8414
sub_9:Test (Best Model) - Loss: 0.0739 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.1815 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.9677 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.0884 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.2956 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.0002 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.3659 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.0849 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.4454 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.8501 - Accuracy: 0.8214 - F1: 0.8170
sub_4:Test (Best Model) - Loss: 0.2417 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.0002 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 1.6427 - Accuracy: 0.7619 - F1: 0.7476
sub_5:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.1311 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 3.2361 - Accuracy: 0.6190 - F1: 0.5544
sub_12:Test (Best Model) - Loss: 0.1919 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.1935 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.4654 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 0.0672 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.4114 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.8619 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.1172 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.8454 - Accuracy: 0.8810 - F1: 0.8792
sub_6:Test (Best Model) - Loss: 0.2889 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 1.2693 - Accuracy: 0.8214 - F1: 0.8155
sub_5:Test (Best Model) - Loss: 1.3074 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.0068 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.0385 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.1172 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.1822 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.6120 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.4221 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.9048 - F1: 0.9045
sub_1:Test (Best Model) - Loss: 0.2337 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.7266 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 1.5252 - Accuracy: 0.7857 - F1: 0.7754
sub_8:Test (Best Model) - Loss: 0.0548 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.3136 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.0024 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.9204 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.1916 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.5504 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.0655 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.1102 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.1916 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.2316 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 1.2407 - Accuracy: 0.8452 - F1: 0.8414
sub_1:Test (Best Model) - Loss: 1.2349 - Accuracy: 0.8214 - F1: 0.8155
sub_8:Test (Best Model) - Loss: 0.0379 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.3922 - Accuracy: 0.9524 - F1: 0.9524
sub_5:Test (Best Model) - Loss: 1.0041 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 1.9351 - Accuracy: 0.7381 - F1: 0.7188
sub_11:Test (Best Model) - Loss: 0.2847 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.1364 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.3925 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.0006 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.0893 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.1018 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.1128 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.3305 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.0958 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.0342 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.4655 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.7128 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.3559 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.8810 - F1: 0.8803
sub_4:Test (Best Model) - Loss: 0.8330 - Accuracy: 0.8571 - F1: 0.8568
sub_3:Test (Best Model) - Loss: 3.2111 - Accuracy: 0.6548 - F1: 0.6080
sub_12:Test (Best Model) - Loss: 0.5155 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 1.2457 - Accuracy: 0.7738 - F1: 0.7616
sub_14:Test (Best Model) - Loss: 0.0789 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.0457 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.1024 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.1796 - Accuracy: 0.9643 - F1: 0.9643
sub_1:Test (Best Model) - Loss: 0.2382 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.0510 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.0003 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.1083 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.2222 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.3376 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.0811 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.0412 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.2474 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.5880 - Accuracy: 0.9286 - F1: 0.9286
sub_7:Test (Best Model) - Loss: 0.2637 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4731 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.0314 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2593 - Accuracy: 0.9286 - F1: 0.9285
sub_2:Test (Best Model) - Loss: 0.2469 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0003 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.3419 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.2166 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.1255 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.1015 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.2484 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.2667 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.2716 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.3381 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4669 - Accuracy: 0.8929 - F1: 0.8925
sub_12:Test (Best Model) - Loss: 0.4565 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.2900 - Accuracy: 0.9167 - F1: 0.9166
sub_14:Test (Best Model) - Loss: 0.0684 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.1475 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.2250 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.1348 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.2275 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.1278 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.3742 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.0173 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 1.0473 - Accuracy: 0.8571 - F1: 0.8542
sub_6:Test (Best Model) - Loss: 0.1025 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.2461 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.1782 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.5456 - Accuracy: 0.9167 - F1: 0.9166
sub_14:Test (Best Model) - Loss: 0.0480 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.0992 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.4308 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.0516 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.9167 - F1: 0.9161
sub_12:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 0.1408 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.0062 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.3368 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.0160 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.1215 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.2042 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.1615 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.1151 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.1422 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 2.0715 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.0131 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.5449 - Accuracy: 0.9167 - F1: 0.9166
sub_5:Test (Best Model) - Loss: 0.3966 - Accuracy: 0.9167 - F1: 0.9164
sub_9:Test (Best Model) - Loss: 1.1094 - Accuracy: 0.8690 - F1: 0.8668
sub_13:Test (Best Model) - Loss: 0.1478 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.2151 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.1356 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.1876 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.2131 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 3.3289 - Accuracy: 0.6429 - F1: 0.5906
sub_10:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.8571 - F1: 0.8551
sub_2:Test (Best Model) - Loss: 0.1966 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.0814 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.3102 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.4355 - Accuracy: 0.9048 - F1: 0.9039
sub_4:Test (Best Model) - Loss: 0.9872 - Accuracy: 0.8690 - F1: 0.8668
sub_5:Test (Best Model) - Loss: 0.2952 - Accuracy: 0.9167 - F1: 0.9166
sub_12:Test (Best Model) - Loss: 0.8476 - Accuracy: 0.9167 - F1: 0.9166
sub_13:Test (Best Model) - Loss: 0.1965 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.5291 - Accuracy: 0.8929 - F1: 0.8927
sub_8:Test (Best Model) - Loss: 0.0221 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.8442 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.8095 - F1: 0.8041
sub_6:Test (Best Model) - Loss: 0.1949 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.2160 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.1500 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.5275 - Accuracy: 0.8095 - F1: 0.8024
sub_4:Test (Best Model) - Loss: 1.1916 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.9167 - F1: 0.9166
sub_13:Test (Best Model) - Loss: 0.0280 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.0675 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.1688 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 2.9607 - Accuracy: 0.7381 - F1: 0.7188
sub_9:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.1194 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.0623 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.0055 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.3142 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.8095 - F1: 0.8024
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.9167 - F1: 0.9164
sub_1:Test (Best Model) - Loss: 0.2817 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.1912 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 2.2471 - Accuracy: 0.7500 - F1: 0.7333
sub_4:Test (Best Model) - Loss: 1.3202 - Accuracy: 0.8452 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 0.1272 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.8929 - F1: 0.8928
sub_1:Test (Best Model) - Loss: 0.2184 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.1247 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 1.0188 - Accuracy: 0.7857 - F1: 0.7754
sub_7:Test (Best Model) - Loss: 0.0393 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 3.0385 - Accuracy: 0.7024 - F1: 0.6735
sub_4:Test (Best Model) - Loss: 0.9770 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.3117 - Accuracy: 0.9167 - F1: 0.9167
sub_3:Test (Best Model) - Loss: 1.5234 - Accuracy: 0.7976 - F1: 0.7890
sub_6:Test (Best Model) - Loss: 0.0052 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.0510 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 2.9879 - Accuracy: 0.6905 - F1: 0.6577
sub_3:Test (Best Model) - Loss: 1.6406 - Accuracy: 0.8214 - F1: 0.8155
sub_6:Test (Best Model) - Loss: 0.3602 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.0408 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.8333 - F1: 0.8286
sub_6:Test (Best Model) - Loss: 0.1302 - Accuracy: 0.9405 - F1: 0.9403

=== Summary Results ===

acc: 92.75 ± 3.76
F1: 92.52 ± 4.10
acc-in: 98.76 ± 0.72
F1-in: 98.75 ± 0.73
