lr: 0.001
sub_13:Test (Best Model) - Loss: 0.2615 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.2509 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 1.2630 - Accuracy: 0.7262 - F1: 0.7079
sub_14:Test (Best Model) - Loss: 1.6471 - Accuracy: 0.7143 - F1: 0.6971
sub_3:Test (Best Model) - Loss: 1.6688 - Accuracy: 0.6310 - F1: 0.5728
sub_5:Test (Best Model) - Loss: 1.7246 - Accuracy: 0.7738 - F1: 0.7712
sub_10:Test (Best Model) - Loss: 0.4265 - Accuracy: 0.9405 - F1: 0.9404
sub_6:Test (Best Model) - Loss: 1.8993 - Accuracy: 0.7857 - F1: 0.7754
sub_12:Test (Best Model) - Loss: 1.2836 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 0.1124 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 1.2173 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 0.2112 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 0.5658 - Accuracy: 0.9167 - F1: 0.9164
sub_13:Test (Best Model) - Loss: 0.5915 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.3640 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.3185 - Accuracy: 0.9405 - F1: 0.9403
sub_5:Test (Best Model) - Loss: 2.1964 - Accuracy: 0.8095 - F1: 0.8024
sub_9:Test (Best Model) - Loss: 3.9128 - Accuracy: 0.7976 - F1: 0.7890
sub_3:Test (Best Model) - Loss: 1.6218 - Accuracy: 0.5119 - F1: 0.3593
sub_10:Test (Best Model) - Loss: 0.2135 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.5530 - Accuracy: 0.8571 - F1: 0.8551
sub_11:Test (Best Model) - Loss: 1.7921 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.7738 - F1: 0.7616
sub_6:Test (Best Model) - Loss: 0.7496 - Accuracy: 0.8690 - F1: 0.8668
sub_4:Test (Best Model) - Loss: 0.5611 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 1.0746 - Accuracy: 0.8929 - F1: 0.8921
sub_14:Test (Best Model) - Loss: 1.8299 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.1423 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 1.1080 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 0.2554 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 0.5076 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.1365 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 1.2100 - Accuracy: 0.8810 - F1: 0.8803
sub_7:Test (Best Model) - Loss: 0.8730 - Accuracy: 0.7976 - F1: 0.7927
sub_11:Test (Best Model) - Loss: 0.7334 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 1.4643 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.4595 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 0.1190 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 1.1217 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.8650 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.8690 - F1: 0.8675
sub_2:Test (Best Model) - Loss: 0.8487 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.0618 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.8214 - F1: 0.8170
sub_11:Test (Best Model) - Loss: 1.7124 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.7619 - F1: 0.7551
sub_1:Test (Best Model) - Loss: 0.8069 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.7353 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.4492 - Accuracy: 0.9167 - F1: 0.9167
sub_9:Test (Best Model) - Loss: 0.0006 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.8571 - F1: 0.8542
sub_4:Test (Best Model) - Loss: 0.3092 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.7024 - F1: 0.6735
sub_5:Test (Best Model) - Loss: 0.9996 - Accuracy: 0.8333 - F1: 0.8299
sub_8:Test (Best Model) - Loss: 0.5107 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 1.1047 - Accuracy: 0.5476 - F1: 0.4312
sub_14:Test (Best Model) - Loss: 1.5751 - Accuracy: 0.8929 - F1: 0.8916
sub_11:Test (Best Model) - Loss: 1.6659 - Accuracy: 0.8810 - F1: 0.8803
sub_7:Test (Best Model) - Loss: 0.4948 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.3888 - Accuracy: 0.9286 - F1: 0.9284
sub_1:Test (Best Model) - Loss: 3.3820 - Accuracy: 0.7738 - F1: 0.7616
sub_10:Test (Best Model) - Loss: 0.9248 - Accuracy: 0.8452 - F1: 0.8414
sub_9:Test (Best Model) - Loss: 0.5076 - Accuracy: 0.8571 - F1: 0.8542
sub_13:Test (Best Model) - Loss: 0.1577 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 1.5884 - Accuracy: 0.7619 - F1: 0.7476
sub_8:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.3123 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.3975 - Accuracy: 0.9286 - F1: 0.9282
sub_7:Test (Best Model) - Loss: 0.4047 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.4569 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 0.7805 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.5226 - Accuracy: 0.7857 - F1: 0.7754
sub_9:Test (Best Model) - Loss: 2.0626 - Accuracy: 0.8571 - F1: 0.8571
sub_10:Test (Best Model) - Loss: 0.1991 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.4329 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.6222 - Accuracy: 0.9524 - F1: 0.9524
sub_3:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.1959 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.5781 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 1.9980 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.0015 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 2.0296 - Accuracy: 0.8095 - F1: 0.8024
sub_4:Test (Best Model) - Loss: 0.3716 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.2513 - Accuracy: 0.9643 - F1: 0.9643
sub_6:Test (Best Model) - Loss: 1.1110 - Accuracy: 0.8690 - F1: 0.8689
sub_9:Test (Best Model) - Loss: 0.0894 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.2474 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.3670 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.2073 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.7588 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 2.1003 - Accuracy: 0.7738 - F1: 0.7616
sub_8:Test (Best Model) - Loss: 0.7932 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.4514 - Accuracy: 0.9048 - F1: 0.9039
sub_2:Test (Best Model) - Loss: 0.7202 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 0.1203 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2790 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 2.1353 - Accuracy: 0.8214 - F1: 0.8212
sub_10:Test (Best Model) - Loss: 0.2371 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.9049 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.8810 - F1: 0.8792
sub_12:Test (Best Model) - Loss: 1.1262 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.0266 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.3935 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.7633 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.2105 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.5623 - Accuracy: 0.7976 - F1: 0.7890
sub_5:Test (Best Model) - Loss: 0.4296 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.3280 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 2.2444 - Accuracy: 0.8452 - F1: 0.8452
sub_10:Test (Best Model) - Loss: 0.4429 - Accuracy: 0.8452 - F1: 0.8442
sub_11:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.9609 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 1.4881 - Accuracy: 0.8690 - F1: 0.8690
sub_8:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.9167 - F1: 0.9164
sub_1:Test (Best Model) - Loss: 0.3060 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.1503 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.0980 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.4866 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.5704 - Accuracy: 0.9048 - F1: 0.9043
sub_5:Test (Best Model) - Loss: 0.2427 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 2.9196 - Accuracy: 0.7619 - F1: 0.7614
sub_14:Test (Best Model) - Loss: 0.2752 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.9525 - Accuracy: 0.8452 - F1: 0.8447
sub_2:Test (Best Model) - Loss: 0.7487 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.5134 - Accuracy: 0.9643 - F1: 0.9643
sub_12:Test (Best Model) - Loss: 1.2268 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.5799 - Accuracy: 0.7619 - F1: 0.7551
sub_13:Test (Best Model) - Loss: 0.0636 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.3729 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 2.4775 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 0.2866 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.8095 - F1: 0.8085
sub_14:Test (Best Model) - Loss: 0.1751 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.2229 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.5875 - Accuracy: 0.8571 - F1: 0.8542
sub_4:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 2.5731 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.5832 - Accuracy: 0.9405 - F1: 0.9405
sub_1:Test (Best Model) - Loss: 1.1357 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 1.7157 - Accuracy: 0.8333 - F1: 0.8330
sub_7:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.9405 - F1: 0.9403
sub_5:Test (Best Model) - Loss: 3.0081 - Accuracy: 0.7619 - F1: 0.7618
sub_2:Test (Best Model) - Loss: 0.0019 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 1.4250 - Accuracy: 0.9048 - F1: 0.9047
sub_11:Test (Best Model) - Loss: 0.2524 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 1.1001 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.8275 - Accuracy: 0.8571 - F1: 0.8551
sub_14:Test (Best Model) - Loss: 3.7726 - Accuracy: 0.5952 - F1: 0.5159
sub_6:Test (Best Model) - Loss: 0.9668 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 2.4599 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.9048 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 1.0127 - Accuracy: 0.8810 - F1: 0.8803
sub_9:Test (Best Model) - Loss: 0.3115 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 0.7543 - Accuracy: 0.8929 - F1: 0.8928
sub_10:Test (Best Model) - Loss: 4.4728 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 1.2025 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 1.2639 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.2031 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.2151 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 1.4762 - Accuracy: 0.8452 - F1: 0.8414
sub_14:Test (Best Model) - Loss: 3.6697 - Accuracy: 0.6071 - F1: 0.5354
sub_1:Test (Best Model) - Loss: 0.4957 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.7436 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.5382 - Accuracy: 0.8571 - F1: 0.8558
sub_5:Test (Best Model) - Loss: 0.3479 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 1.1672 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.1036 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.0422 - Accuracy: 0.6905 - F1: 0.6577
sub_12:Test (Best Model) - Loss: 1.8925 - Accuracy: 0.9048 - F1: 0.9047
sub_11:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.8376 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.8943 - Accuracy: 0.9286 - F1: 0.9286
sub_14:Test (Best Model) - Loss: 2.2684 - Accuracy: 0.5476 - F1: 0.4312
sub_13:Test (Best Model) - Loss: 0.2434 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.5667 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 1.9216 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.7262 - F1: 0.7040
sub_7:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.6905 - F1: 0.6816
sub_5:Test (Best Model) - Loss: 0.5115 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 1.5141 - Accuracy: 0.7738 - F1: 0.7616
sub_12:Test (Best Model) - Loss: 2.4869 - Accuracy: 0.8690 - F1: 0.8675
sub_14:Test (Best Model) - Loss: 6.7590 - Accuracy: 0.5357 - F1: 0.4081
sub_1:Test (Best Model) - Loss: 0.1624 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 1.5063 - Accuracy: 0.7262 - F1: 0.7040
sub_6:Test (Best Model) - Loss: 1.9371 - Accuracy: 0.7976 - F1: 0.7890
sub_7:Test (Best Model) - Loss: 1.0360 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 1.5826 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.8810 - F1: 0.8803
sub_14:Test (Best Model) - Loss: 2.5811 - Accuracy: 0.6071 - F1: 0.5354
sub_2:Test (Best Model) - Loss: 1.6442 - Accuracy: 0.8810 - F1: 0.8799
sub_4:Test (Best Model) - Loss: 2.1726 - Accuracy: 0.8214 - F1: 0.8155
sub_6:Test (Best Model) - Loss: 0.3146 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 1.7728 - Accuracy: 0.8333 - F1: 0.8299
sub_4:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.8452 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 1.5185 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 1.9219 - Accuracy: 0.6786 - F1: 0.6415
sub_6:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.7500 - F1: 0.7393

=== Summary Results ===

acc: 87.83 ± 5.49
F1: 87.02 ± 6.52
acc-in: 98.43 ± 0.98
F1-in: 98.41 ± 1.00
