lr: 0.001
sub_11:Test (Best Model) - Loss: 0.5716 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.2343 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.0088 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.2308 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.4400 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 1.8190 - Accuracy: 0.7976 - F1: 0.7890
sub_3:Test (Best Model) - Loss: 2.5148 - Accuracy: 0.6667 - F1: 0.6250
sub_4:Test (Best Model) - Loss: 0.8729 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.5298 - Accuracy: 0.9643 - F1: 0.9643
sub_5:Test (Best Model) - Loss: 1.0458 - Accuracy: 0.8810 - F1: 0.8803
sub_12:Test (Best Model) - Loss: 0.1392 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.7985 - Accuracy: 0.9167 - F1: 0.9164
sub_6:Test (Best Model) - Loss: 1.1590 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.0891 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.7692 - Accuracy: 0.9048 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.1622 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 2.4406 - Accuracy: 0.8095 - F1: 0.8024
sub_4:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 1.2304 - Accuracy: 0.8571 - F1: 0.8542
sub_5:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.8571 - F1: 0.8558
sub_7:Test (Best Model) - Loss: 0.3136 - Accuracy: 0.9405 - F1: 0.9405
sub_14:Test (Best Model) - Loss: 0.8936 - Accuracy: 0.8929 - F1: 0.8928
sub_6:Test (Best Model) - Loss: 0.7336 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 1.9995 - Accuracy: 0.8452 - F1: 0.8425
sub_11:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.0743 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.1875 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 2.0662 - Accuracy: 0.8095 - F1: 0.8024
sub_1:Test (Best Model) - Loss: 1.2573 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 1.2880 - Accuracy: 0.8690 - F1: 0.8689
sub_7:Test (Best Model) - Loss: 0.3594 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.8690 - F1: 0.8686
sub_12:Test (Best Model) - Loss: 0.5152 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 0.6021 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4350 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 1.1631 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.1363 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 0.8762 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.3694 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 1.7822 - Accuracy: 0.8095 - F1: 0.8041
sub_6:Test (Best Model) - Loss: 0.1250 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.4051 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 1.1000 - Accuracy: 0.8214 - F1: 0.8155
sub_11:Test (Best Model) - Loss: 0.3891 - Accuracy: 0.9524 - F1: 0.9524
sub_5:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.8810 - F1: 0.8807
sub_13:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.8452 - F1: 0.8414
sub_8:Test (Best Model) - Loss: 0.2440 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.6156 - Accuracy: 0.9048 - F1: 0.9043
sub_9:Test (Best Model) - Loss: 0.1061 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 2.2671 - Accuracy: 0.8452 - F1: 0.8414
sub_14:Test (Best Model) - Loss: 1.4165 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 2.6861 - Accuracy: 0.7738 - F1: 0.7616
sub_3:Test (Best Model) - Loss: 2.8553 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.8968 - Accuracy: 0.8571 - F1: 0.8542
sub_4:Test (Best Model) - Loss: 0.4301 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.5533 - Accuracy: 0.8690 - F1: 0.8675
sub_11:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 3.5085 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 1.3129 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.3725 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 2.2534 - Accuracy: 0.7976 - F1: 0.7962
sub_6:Test (Best Model) - Loss: 0.3616 - Accuracy: 0.9405 - F1: 0.9405
sub_10:Test (Best Model) - Loss: 1.8570 - Accuracy: 0.8571 - F1: 0.8551
sub_12:Test (Best Model) - Loss: 0.8900 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.4556 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.2295 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.4822 - Accuracy: 0.7976 - F1: 0.7890
sub_11:Test (Best Model) - Loss: 0.0694 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.2626 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.5820 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.1161 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.2794 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.5358 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.1865 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.1435 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.2844 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.7619 - F1: 0.7529
sub_2:Test (Best Model) - Loss: 0.7990 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.2679 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.1900 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.3960 - Accuracy: 0.9048 - F1: 0.9045
sub_10:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.4706 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.9706 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 1.0944 - Accuracy: 0.8810 - F1: 0.8807
sub_14:Test (Best Model) - Loss: 0.2362 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.8979 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.2089 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.2320 - Accuracy: 0.9405 - F1: 0.9403
sub_6:Test (Best Model) - Loss: 0.5968 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 3.2087 - Accuracy: 0.6429 - F1: 0.6396
sub_11:Test (Best Model) - Loss: 0.2147 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.4245 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.3233 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.3199 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 1.0291 - Accuracy: 0.7976 - F1: 0.7927
sub_13:Test (Best Model) - Loss: 0.4196 - Accuracy: 0.9167 - F1: 0.9161
sub_4:Test (Best Model) - Loss: 0.9573 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.1600 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.1372 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.1327 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 1.1536 - Accuracy: 0.9048 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 0.5282 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.9358 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 3.5576 - Accuracy: 0.6429 - F1: 0.6396
sub_13:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.3310 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.4937 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.5592 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.5196 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 1.2993 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 1.6281 - Accuracy: 0.9048 - F1: 0.9045
sub_13:Test (Best Model) - Loss: 0.1602 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.2206 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.9876 - Accuracy: 0.8810 - F1: 0.8792
sub_1:Test (Best Model) - Loss: 0.3273 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.0520 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.3133 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.1751 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.9048 - F1: 0.9039
sub_2:Test (Best Model) - Loss: 0.3235 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 1.1589 - Accuracy: 0.8929 - F1: 0.8921
sub_11:Test (Best Model) - Loss: 0.1587 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.7780 - Accuracy: 0.9167 - F1: 0.9164
sub_9:Test (Best Model) - Loss: 0.8295 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.1859 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.1151 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.2983 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 2.7319 - Accuracy: 0.7024 - F1: 0.6735
sub_4:Test (Best Model) - Loss: 0.5333 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 1.4816 - Accuracy: 0.8333 - F1: 0.8286
sub_10:Test (Best Model) - Loss: 0.6077 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.5272 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.2621 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.2173 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.1424 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.9228 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.8964 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 1.4731 - Accuracy: 0.7262 - F1: 0.7040
sub_3:Test (Best Model) - Loss: 2.0416 - Accuracy: 0.8095 - F1: 0.8024
sub_1:Test (Best Model) - Loss: 1.2115 - Accuracy: 0.9048 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.9660 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.6016 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.5050 - Accuracy: 0.8929 - F1: 0.8925
sub_12:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.9286 - F1: 0.9285
sub_9:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.2314 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.3503 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 3.6089 - Accuracy: 0.7738 - F1: 0.7616
sub_7:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.7857 - F1: 0.7754
sub_10:Test (Best Model) - Loss: 1.5320 - Accuracy: 0.7262 - F1: 0.7040
sub_8:Test (Best Model) - Loss: 0.5208 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.2784 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.1991 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.1314 - Accuracy: 0.7619 - F1: 0.7569
sub_12:Test (Best Model) - Loss: 0.5641 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.8333 - F1: 0.8299
sub_11:Test (Best Model) - Loss: 0.0607 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.5939 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 1.5476 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 1.8113 - Accuracy: 0.7976 - F1: 0.7890
sub_5:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.5684 - Accuracy: 0.8571 - F1: 0.8571
sub_10:Test (Best Model) - Loss: 1.5515 - Accuracy: 0.6667 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.1205 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.5603 - Accuracy: 0.7619 - F1: 0.7476
sub_12:Test (Best Model) - Loss: 1.7384 - Accuracy: 0.8929 - F1: 0.8927
sub_9:Test (Best Model) - Loss: 0.5130 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.8697 - Accuracy: 0.5833 - F1: 0.5819
sub_4:Test (Best Model) - Loss: 2.3554 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 1.5205 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.3535 - Accuracy: 0.9405 - F1: 0.9405
sub_7:Test (Best Model) - Loss: 0.8091 - Accuracy: 0.7381 - F1: 0.7326
sub_1:Test (Best Model) - Loss: 0.2691 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.9393 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.0035 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.2796 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 1.8115 - Accuracy: 0.8214 - F1: 0.8183
sub_14:Test (Best Model) - Loss: 2.5314 - Accuracy: 0.7262 - F1: 0.7040
sub_6:Test (Best Model) - Loss: 1.0136 - Accuracy: 0.7143 - F1: 0.6889
sub_5:Test (Best Model) - Loss: 1.0222 - Accuracy: 0.8929 - F1: 0.8925
sub_1:Test (Best Model) - Loss: 0.6394 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.5789 - Accuracy: 0.7381 - F1: 0.7357
sub_4:Test (Best Model) - Loss: 1.9267 - Accuracy: 0.8214 - F1: 0.8155
sub_6:Test (Best Model) - Loss: 0.4378 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.5330 - Accuracy: 0.8333 - F1: 0.8286
sub_1:Test (Best Model) - Loss: 0.4128 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.8535 - Accuracy: 0.6071 - F1: 0.6044
sub_4:Test (Best Model) - Loss: 0.1378 - Accuracy: 0.9762 - F1: 0.9762

=== Summary Results ===

acc: 89.90 ± 3.67
F1: 89.64 ± 3.87
acc-in: 98.53 ± 1.34
F1-in: 98.51 ± 1.37
