lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4286 - F1: 0.3166
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.7500 - F1: 0.7393
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.4081
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5714 - F1: 0.5333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5357 - F1: 0.4382
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5119 - F1: 0.3593
sub_2:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6905 - F1: 0.6577
sub_2:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.8452 - F1: 0.8442
sub_2:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.7976 - F1: 0.7962
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.7738 - F1: 0.7730
sub_2:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.7143 - F1: 0.7035
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.6667 - F1: 0.6571
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3875
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4881 - F1: 0.4874
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6905 - F1: 0.6630
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5476 - F1: 0.4312
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.7024 - F1: 0.6825
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.6071 - F1: 0.5452
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3534
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5833 - F1: 0.5353
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4643 - F1: 0.3665
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4524 - F1: 0.3115
sub_4:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5595 - F1: 0.5167
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5238 - F1: 0.4430
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4048 - F1: 0.3690
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6429 - F1: 0.6327
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4881 - F1: 0.3649
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3875
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5952 - F1: 0.5915
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5595 - F1: 0.4999
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5238 - F1: 0.3842
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5833 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.6071 - F1: 0.5753
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3534
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5238 - F1: 0.3842
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5952 - F1: 0.5265
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5952 - F1: 0.5800
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5833 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5119 - F1: 0.4349
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.6190 - F1: 0.5544
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5952 - F1: 0.5800
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5833 - F1: 0.5761
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5833 - F1: 0.5073
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5714 - F1: 0.5088
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4167 - F1: 0.4099
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3713
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6190 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5833 - F1: 0.4958
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6786 - F1: 0.6763
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5595 - F1: 0.4535
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3534
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5119 - F1: 0.4094
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.6905 - F1: 0.6677
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5833 - F1: 0.4958
sub_8:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5595 - F1: 0.4535
sub_8:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5714 - F1: 0.4750
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5357 - F1: 0.4906
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4524 - F1: 0.4474
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.4269
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5238 - F1: 0.4305
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4405 - F1: 0.3058
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4881 - F1: 0.4074
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5476 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.4974
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4405 - F1: 0.3861
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4762 - F1: 0.4510
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4643 - F1: 0.4414
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5595 - F1: 0.4535
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6310 - F1: 0.6245
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.4239
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5238 - F1: 0.4013
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4286 - F1: 0.3571
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4167 - F1: 0.3495
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5119 - F1: 0.4645
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.3810 - F1: 0.2759
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.4081
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.6310 - F1: 0.6305
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5595 - F1: 0.5167
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.7143 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.4239
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5476 - F1: 0.5306
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333

=== Summary Results ===

acc: 52.45 ± 3.44
F1: 39.80 ± 5.08
acc-in: 56.98 ± 5.38
F1-in: 47.00 ± 8.09
