lr: 1e-05
sub_14:Test (Best Model) - Loss: 0.2529 - Accuracy: 0.8690 - F1: 0.8689
sub_8:Test (Best Model) - Loss: 0.0412 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.7857 - F1: 0.7754
sub_10:Test (Best Model) - Loss: 0.1470 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.0888 - Accuracy: 0.9643 - F1: 0.9643
sub_9:Test (Best Model) - Loss: 0.0846 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.1814 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.1593 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.1839 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.1527 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.7024 - F1: 0.6735
sub_14:Test (Best Model) - Loss: 0.2685 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.1089 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.1304 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 0.1143 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.0935 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.2810 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 0.2288 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.2997 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.3043 - Accuracy: 0.9048 - F1: 0.9043
sub_14:Test (Best Model) - Loss: 0.3042 - Accuracy: 0.8810 - F1: 0.8809
sub_10:Test (Best Model) - Loss: 0.2019 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.0411 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.0658 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.1638 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 0.0730 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.2995 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 0.1469 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.3987 - Accuracy: 0.7976 - F1: 0.7969
sub_6:Test (Best Model) - Loss: 0.2324 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.1856 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.1963 - Accuracy: 0.9286 - F1: 0.9285
sub_3:Test (Best Model) - Loss: 0.2533 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 0.2169 - Accuracy: 0.8929 - F1: 0.8925
sub_11:Test (Best Model) - Loss: 0.0829 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.0453 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.1354 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 1.0479 - Accuracy: 0.7738 - F1: 0.7683
sub_6:Test (Best Model) - Loss: 0.1673 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.0428 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.0192 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.2829 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.2472 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.2195 - Accuracy: 0.9167 - F1: 0.9164
sub_7:Test (Best Model) - Loss: 0.3069 - Accuracy: 0.8571 - F1: 0.8564
sub_1:Test (Best Model) - Loss: 0.3301 - Accuracy: 0.8571 - F1: 0.8542
sub_10:Test (Best Model) - Loss: 0.1274 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.8095 - F1: 0.8041
sub_8:Test (Best Model) - Loss: 0.0905 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2026 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.0524 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.2948 - Accuracy: 0.8571 - F1: 0.8551
sub_3:Test (Best Model) - Loss: 0.3011 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.2235 - Accuracy: 0.9048 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 0.7323 - Accuracy: 0.7738 - F1: 0.7616
sub_8:Test (Best Model) - Loss: 0.0129 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.2228 - Accuracy: 0.9286 - F1: 0.9282
sub_11:Test (Best Model) - Loss: 0.2313 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.2533 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.1985 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.1200 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.5584 - Accuracy: 0.8690 - F1: 0.8668
sub_7:Test (Best Model) - Loss: 0.2554 - Accuracy: 0.8690 - F1: 0.8686
sub_14:Test (Best Model) - Loss: 0.2033 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.0234 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2856 - Accuracy: 0.9167 - F1: 0.9167
sub_1:Test (Best Model) - Loss: 0.0765 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.3001 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.0173 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.4013 - Accuracy: 0.8452 - F1: 0.8425
sub_13:Test (Best Model) - Loss: 0.4446 - Accuracy: 0.7976 - F1: 0.7890
sub_6:Test (Best Model) - Loss: 0.3273 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 0.1250 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.0900 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.3077 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.0108 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.1784 - Accuracy: 0.9286 - F1: 0.9285
sub_3:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.7500 - F1: 0.7333
sub_11:Test (Best Model) - Loss: 0.1114 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.2729 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.0701 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.2312 - Accuracy: 0.8810 - F1: 0.8792
sub_6:Test (Best Model) - Loss: 0.2369 - Accuracy: 0.9048 - F1: 0.9047
sub_2:Test (Best Model) - Loss: 0.4011 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 0.1638 - Accuracy: 0.9048 - F1: 0.9045
sub_10:Test (Best Model) - Loss: 0.0590 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.0640 - Accuracy: 0.9643 - F1: 0.9643
sub_5:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.8095 - F1: 0.8056
sub_1:Test (Best Model) - Loss: 0.1837 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.2302 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.0096 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.1093 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.0791 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.1953 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.2471 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.2331 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.0899 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.5233 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.4517 - Accuracy: 0.7857 - F1: 0.7754
sub_6:Test (Best Model) - Loss: 0.3256 - Accuracy: 0.8333 - F1: 0.8286
sub_4:Test (Best Model) - Loss: 0.2148 - Accuracy: 0.8929 - F1: 0.8921
sub_13:Test (Best Model) - Loss: 0.1338 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.2622 - Accuracy: 0.8690 - F1: 0.8668
sub_5:Test (Best Model) - Loss: 0.5115 - Accuracy: 0.7857 - F1: 0.7852
sub_12:Test (Best Model) - Loss: 0.3281 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.0353 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.3999 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.0636 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.2214 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 0.2565 - Accuracy: 0.9167 - F1: 0.9161
sub_4:Test (Best Model) - Loss: 0.3302 - Accuracy: 0.8929 - F1: 0.8921
sub_6:Test (Best Model) - Loss: 0.4947 - Accuracy: 0.8095 - F1: 0.8024
sub_3:Test (Best Model) - Loss: 0.1411 - Accuracy: 0.9405 - F1: 0.9404
sub_8:Test (Best Model) - Loss: 0.2338 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.5833 - F1: 0.4958
sub_11:Test (Best Model) - Loss: 0.0742 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.0560 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.1222 - Accuracy: 0.9405 - F1: 0.9405
sub_13:Test (Best Model) - Loss: 0.1231 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.9200 - Accuracy: 0.6667 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 0.1948 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.0892 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.2194 - Accuracy: 0.8929 - F1: 0.8928
sub_10:Test (Best Model) - Loss: 1.1241 - Accuracy: 0.6071 - F1: 0.5354
sub_4:Test (Best Model) - Loss: 0.3811 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 0.1076 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.1833 - Accuracy: 0.9286 - F1: 0.9286
sub_11:Test (Best Model) - Loss: 0.0915 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.1266 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.5595 - F1: 0.4535
sub_6:Test (Best Model) - Loss: 0.1807 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.5249 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6786 - F1: 0.6415
sub_1:Test (Best Model) - Loss: 0.2088 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.1938 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.0691 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.4935 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.1098 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.4795 - Accuracy: 0.7976 - F1: 0.7976
sub_12:Test (Best Model) - Loss: 0.3286 - Accuracy: 0.8571 - F1: 0.8564
sub_10:Test (Best Model) - Loss: 0.5333 - Accuracy: 0.7262 - F1: 0.7040
sub_14:Test (Best Model) - Loss: 1.2018 - Accuracy: 0.6190 - F1: 0.5544
sub_8:Test (Best Model) - Loss: 0.2523 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.2881 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.1830 - Accuracy: 0.9048 - F1: 0.9045
sub_5:Test (Best Model) - Loss: 0.1419 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.1039 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.4118 - Accuracy: 0.8095 - F1: 0.8041
sub_12:Test (Best Model) - Loss: 0.4097 - Accuracy: 0.8214 - F1: 0.8183
sub_11:Test (Best Model) - Loss: 0.0664 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.1588 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.7720 - Accuracy: 0.6786 - F1: 0.6415
sub_14:Test (Best Model) - Loss: 1.4817 - Accuracy: 0.6310 - F1: 0.5728
sub_2:Test (Best Model) - Loss: 0.0723 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.9236 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.4377 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.1616 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.1764 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.1531 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.3648 - Accuracy: 0.8452 - F1: 0.8414
sub_7:Test (Best Model) - Loss: 0.1857 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.0853 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.7381 - F1: 0.7188
sub_11:Test (Best Model) - Loss: 0.0462 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.0844 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.1055 - Accuracy: 0.9405 - F1: 0.9403
sub_6:Test (Best Model) - Loss: 0.5776 - Accuracy: 0.7262 - F1: 0.7040
sub_11:Test (Best Model) - Loss: 0.0743 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.1830 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.4046 - Accuracy: 0.8571 - F1: 0.8542
sub_3:Test (Best Model) - Loss: 0.2236 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.2570 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.5044 - Accuracy: 0.7143 - F1: 0.7141
sub_13:Test (Best Model) - Loss: 0.0689 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.1318 - Accuracy: 0.9643 - F1: 0.9643
sub_9:Test (Best Model) - Loss: 0.5441 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.3233 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.0755 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.0437 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.1342 - Accuracy: 0.9286 - F1: 0.9285
sub_5:Test (Best Model) - Loss: 0.2405 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.3271 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.0470 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.0770 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.2884 - Accuracy: 0.8333 - F1: 0.8318
sub_3:Test (Best Model) - Loss: 0.6201 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.4564 - Accuracy: 0.8214 - F1: 0.8214
sub_13:Test (Best Model) - Loss: 0.0855 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.4284 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 0.5408 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.1674 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.0519 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5459 - Accuracy: 0.7500 - F1: 0.7418
sub_5:Test (Best Model) - Loss: 0.5013 - Accuracy: 0.8571 - F1: 0.8564
sub_3:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.0398 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.7262 - F1: 0.7040
sub_7:Test (Best Model) - Loss: 0.2542 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 0.1225 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.3280 - Accuracy: 0.8452 - F1: 0.8452
sub_7:Test (Best Model) - Loss: 0.4170 - Accuracy: 0.7619 - F1: 0.7476
sub_3:Test (Best Model) - Loss: 0.5304 - Accuracy: 0.7381 - F1: 0.7224
sub_1:Test (Best Model) - Loss: 0.1566 - Accuracy: 0.9405 - F1: 0.9403
sub_5:Test (Best Model) - Loss: 0.3227 - Accuracy: 0.8690 - F1: 0.8690
sub_7:Test (Best Model) - Loss: 0.3968 - Accuracy: 0.8095 - F1: 0.8056
sub_5:Test (Best Model) - Loss: 0.2798 - Accuracy: 0.8810 - F1: 0.8810

=== Summary Results ===

acc: 89.40 ± 4.79
F1: 88.94 ± 5.29
acc-in: 96.07 ± 2.53
F1-in: 95.98 ± 2.68
