lr: 1e-06
sub_11:Test (Best Model) - Loss: 1.1873 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.5884 - Accuracy: 0.6905 - F1: 0.6756
sub_10:Test (Best Model) - Loss: 0.8965 - Accuracy: 0.5476 - F1: 0.4312
sub_7:Test (Best Model) - Loss: 0.7852 - Accuracy: 0.5833 - F1: 0.5696
sub_13:Test (Best Model) - Loss: 1.2509 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.8550 - Accuracy: 0.5357 - F1: 0.4510
sub_8:Test (Best Model) - Loss: 0.2737 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.5650 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.5427 - Accuracy: 0.6667 - F1: 0.6313
sub_9:Test (Best Model) - Loss: 0.3667 - Accuracy: 0.8690 - F1: 0.8675
sub_2:Test (Best Model) - Loss: 0.2040 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.5160 - Accuracy: 0.7857 - F1: 0.7857
sub_7:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6071 - F1: 0.6044
sub_3:Test (Best Model) - Loss: 0.8116 - Accuracy: 0.5476 - F1: 0.4458
sub_1:Test (Best Model) - Loss: 0.7917 - Accuracy: 0.5714 - F1: 0.5333
sub_11:Test (Best Model) - Loss: 0.4088 - Accuracy: 0.7976 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 0.3175 - Accuracy: 0.9048 - F1: 0.9048
sub_6:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6071 - F1: 0.6071
sub_13:Test (Best Model) - Loss: 0.4281 - Accuracy: 0.7976 - F1: 0.7941
sub_10:Test (Best Model) - Loss: 0.3502 - Accuracy: 0.8333 - F1: 0.8318
sub_7:Test (Best Model) - Loss: 0.8679 - Accuracy: 0.5595 - F1: 0.4791
sub_5:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.7262 - F1: 0.7114
sub_6:Test (Best Model) - Loss: 0.9161 - Accuracy: 0.4881 - F1: 0.3806
sub_13:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5952 - F1: 0.5524
sub_8:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.6667 - F1: 0.6636
sub_9:Test (Best Model) - Loss: 0.5031 - Accuracy: 0.8095 - F1: 0.8091
sub_3:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.2845 - Accuracy: 0.9405 - F1: 0.9404
sub_10:Test (Best Model) - Loss: 1.0152 - Accuracy: 0.4286 - F1: 0.3778
sub_7:Test (Best Model) - Loss: 0.8472 - Accuracy: 0.6429 - F1: 0.5906
sub_11:Test (Best Model) - Loss: 0.2962 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.4290 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.5952 - F1: 0.5265
sub_5:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.6905 - F1: 0.6788
sub_12:Test (Best Model) - Loss: 0.4600 - Accuracy: 0.7738 - F1: 0.7641
sub_6:Test (Best Model) - Loss: 0.4463 - Accuracy: 0.7857 - F1: 0.7776
sub_2:Test (Best Model) - Loss: 0.3808 - Accuracy: 0.8333 - F1: 0.8325
sub_3:Test (Best Model) - Loss: 0.6017 - Accuracy: 0.7024 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.4358 - Accuracy: 0.8333 - F1: 0.8333
sub_4:Test (Best Model) - Loss: 0.3986 - Accuracy: 0.8333 - F1: 0.8330
sub_7:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.6667 - F1: 0.6313
sub_8:Test (Best Model) - Loss: 0.2595 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.5284 - Accuracy: 0.7381 - F1: 0.7368
sub_5:Test (Best Model) - Loss: 0.7566 - Accuracy: 0.4524 - F1: 0.4524
sub_9:Test (Best Model) - Loss: 0.2064 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4152 - Accuracy: 0.8095 - F1: 0.8091
sub_7:Test (Best Model) - Loss: 0.5082 - Accuracy: 0.7381 - F1: 0.7381
sub_1:Test (Best Model) - Loss: 0.5090 - Accuracy: 0.7857 - F1: 0.7856
sub_3:Test (Best Model) - Loss: 0.4256 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.5111 - Accuracy: 0.7619 - F1: 0.7597
sub_10:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.8571 - F1: 0.8558
sub_4:Test (Best Model) - Loss: 0.7800 - Accuracy: 0.4881 - F1: 0.4792
sub_2:Test (Best Model) - Loss: 0.5195 - Accuracy: 0.7619 - F1: 0.7476
sub_13:Test (Best Model) - Loss: 0.8808 - Accuracy: 0.5000 - F1: 0.4020
sub_12:Test (Best Model) - Loss: 0.3583 - Accuracy: 0.8929 - F1: 0.8928
sub_5:Test (Best Model) - Loss: 0.8790 - Accuracy: 0.5595 - F1: 0.5238
sub_8:Test (Best Model) - Loss: 0.2455 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.2570 - Accuracy: 0.9286 - F1: 0.9284
sub_4:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5595 - F1: 0.4999
sub_5:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6429 - F1: 0.6420
sub_7:Test (Best Model) - Loss: 0.7419 - Accuracy: 0.5714 - F1: 0.5553
sub_6:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.6429 - F1: 0.5982
sub_1:Test (Best Model) - Loss: 0.7918 - Accuracy: 0.4881 - F1: 0.4822
sub_9:Test (Best Model) - Loss: 0.2998 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.3768 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 0.5752 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.4202 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.3602 - Accuracy: 0.8571 - F1: 0.8568
sub_3:Test (Best Model) - Loss: 0.4263 - Accuracy: 0.8333 - F1: 0.8330
sub_10:Test (Best Model) - Loss: 0.7519 - Accuracy: 0.6310 - F1: 0.6063
sub_8:Test (Best Model) - Loss: 0.1815 - Accuracy: 0.9405 - F1: 0.9405
sub_2:Test (Best Model) - Loss: 0.3885 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6310 - F1: 0.5884
sub_11:Test (Best Model) - Loss: 0.5478 - Accuracy: 0.8095 - F1: 0.8068
sub_4:Test (Best Model) - Loss: 0.3269 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.8357 - Accuracy: 0.6190 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 0.4961 - Accuracy: 0.7619 - F1: 0.7529
sub_14:Test (Best Model) - Loss: 0.4336 - Accuracy: 0.8333 - F1: 0.8318
sub_6:Test (Best Model) - Loss: 0.9336 - Accuracy: 0.5119 - F1: 0.4557
sub_3:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.6310 - F1: 0.6267
sub_1:Test (Best Model) - Loss: 0.4800 - Accuracy: 0.7619 - F1: 0.7476
sub_5:Test (Best Model) - Loss: 0.4950 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 0.5957 - Accuracy: 0.6905 - F1: 0.6903
sub_8:Test (Best Model) - Loss: 0.0785 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.5952 - F1: 0.5837
sub_5:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.5714 - F1: 0.5508
sub_10:Test (Best Model) - Loss: 0.3946 - Accuracy: 0.8452 - F1: 0.8434
sub_12:Test (Best Model) - Loss: 0.5055 - Accuracy: 0.7500 - F1: 0.7456
sub_2:Test (Best Model) - Loss: 0.2514 - Accuracy: 0.9286 - F1: 0.9284
sub_3:Test (Best Model) - Loss: 0.9465 - Accuracy: 0.3571 - F1: 0.3538
sub_4:Test (Best Model) - Loss: 0.3414 - Accuracy: 0.8571 - F1: 0.8558
sub_11:Test (Best Model) - Loss: 0.1723 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.3159 - Accuracy: 0.8452 - F1: 0.8414
sub_7:Test (Best Model) - Loss: 0.2965 - Accuracy: 0.9048 - F1: 0.9047
sub_3:Test (Best Model) - Loss: 0.8572 - Accuracy: 0.4643 - F1: 0.4286
sub_13:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.7619 - F1: 0.7597
sub_5:Test (Best Model) - Loss: 0.9218 - Accuracy: 0.5476 - F1: 0.4312
sub_9:Test (Best Model) - Loss: 0.3537 - Accuracy: 0.8452 - F1: 0.8434
sub_6:Test (Best Model) - Loss: 0.7196 - Accuracy: 0.5476 - F1: 0.4911
sub_14:Test (Best Model) - Loss: 0.4999 - Accuracy: 0.7976 - F1: 0.7974
sub_7:Test (Best Model) - Loss: 0.8259 - Accuracy: 0.5357 - F1: 0.4906
sub_13:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.6667 - F1: 0.6250
sub_10:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.6071 - F1: 0.6026
sub_1:Test (Best Model) - Loss: 0.3545 - Accuracy: 0.8095 - F1: 0.8024
sub_11:Test (Best Model) - Loss: 0.3641 - Accuracy: 0.8571 - F1: 0.8551
sub_2:Test (Best Model) - Loss: 0.4971 - Accuracy: 0.7738 - F1: 0.7616
sub_12:Test (Best Model) - Loss: 0.4953 - Accuracy: 0.7619 - F1: 0.7504
sub_8:Test (Best Model) - Loss: 0.1427 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.2896 - Accuracy: 0.8810 - F1: 0.8799
sub_14:Test (Best Model) - Loss: 0.5688 - Accuracy: 0.6548 - F1: 0.6150
sub_5:Test (Best Model) - Loss: 0.4832 - Accuracy: 0.7738 - F1: 0.7730
sub_4:Test (Best Model) - Loss: 0.2664 - Accuracy: 0.8929 - F1: 0.8916
sub_3:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.7857 - F1: 0.7838
sub_7:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.5714 - F1: 0.5088
sub_13:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.6310 - F1: 0.6245
sub_11:Test (Best Model) - Loss: 0.2993 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.2256 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.3163 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.4553 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.4944 - Accuracy: 0.7381 - F1: 0.7306
sub_5:Test (Best Model) - Loss: 1.0481 - Accuracy: 0.4643 - F1: 0.3171
sub_9:Test (Best Model) - Loss: 0.2502 - Accuracy: 0.9167 - F1: 0.9164
sub_7:Test (Best Model) - Loss: 0.8075 - Accuracy: 0.5595 - F1: 0.4670
sub_8:Test (Best Model) - Loss: 0.1165 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.3123 - Accuracy: 0.8810 - F1: 0.8809
sub_14:Test (Best Model) - Loss: 0.4605 - Accuracy: 0.7857 - F1: 0.7754
sub_7:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.6071 - F1: 0.5354
sub_1:Test (Best Model) - Loss: 0.6254 - Accuracy: 0.6548 - F1: 0.6080
sub_13:Test (Best Model) - Loss: 0.2968 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.2863 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.8553 - Accuracy: 0.4286 - F1: 0.4204
sub_2:Test (Best Model) - Loss: 0.3007 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 0.5435 - Accuracy: 0.6548 - F1: 0.6150
sub_5:Test (Best Model) - Loss: 0.5436 - Accuracy: 0.7619 - F1: 0.7607
sub_12:Test (Best Model) - Loss: 0.2193 - Accuracy: 0.9286 - F1: 0.9286
sub_7:Test (Best Model) - Loss: 0.8736 - Accuracy: 0.4048 - F1: 0.3690
sub_4:Test (Best Model) - Loss: 0.4054 - Accuracy: 0.8333 - F1: 0.8318
sub_6:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.7619 - F1: 0.7476
sub_8:Test (Best Model) - Loss: 0.2716 - Accuracy: 0.9167 - F1: 0.9167
sub_9:Test (Best Model) - Loss: 0.4270 - Accuracy: 0.7738 - F1: 0.7616
sub_7:Test (Best Model) - Loss: 1.0084 - Accuracy: 0.3690 - F1: 0.3270
sub_10:Test (Best Model) - Loss: 1.1632 - Accuracy: 0.5119 - F1: 0.3944
sub_14:Test (Best Model) - Loss: 0.3657 - Accuracy: 0.8690 - F1: 0.8689
sub_11:Test (Best Model) - Loss: 0.3259 - Accuracy: 0.8810 - F1: 0.8799
sub_1:Test (Best Model) - Loss: 0.4668 - Accuracy: 0.7381 - F1: 0.7255
sub_5:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.4766 - Accuracy: 0.7500 - F1: 0.7491
sub_3:Test (Best Model) - Loss: 0.8865 - Accuracy: 0.5357 - F1: 0.4081
sub_9:Test (Best Model) - Loss: 0.9657 - Accuracy: 0.4286 - F1: 0.3571
sub_5:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.4643 - F1: 0.3353
sub_2:Test (Best Model) - Loss: 0.4974 - Accuracy: 0.7738 - F1: 0.7616
sub_6:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.7619 - F1: 0.7619
sub_8:Test (Best Model) - Loss: 0.2173 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 0.4811 - Accuracy: 0.8095 - F1: 0.8068
sub_12:Test (Best Model) - Loss: 0.2792 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 0.7969 - Accuracy: 0.5595 - F1: 0.4791
sub_14:Test (Best Model) - Loss: 0.8763 - Accuracy: 0.5476 - F1: 0.4458
sub_3:Test (Best Model) - Loss: 0.9260 - Accuracy: 0.5238 - F1: 0.4643
sub_4:Test (Best Model) - Loss: 0.2963 - Accuracy: 0.9048 - F1: 0.9043
sub_13:Test (Best Model) - Loss: 0.3106 - Accuracy: 0.9048 - F1: 0.9047
sub_1:Test (Best Model) - Loss: 0.5726 - Accuracy: 0.6548 - F1: 0.6543
sub_10:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6429 - F1: 0.6396
sub_2:Test (Best Model) - Loss: 0.3472 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.4204 - Accuracy: 0.8214 - F1: 0.8194
sub_9:Test (Best Model) - Loss: 0.4182 - Accuracy: 0.8214 - F1: 0.8155
sub_11:Test (Best Model) - Loss: 0.2816 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6190 - F1: 0.5634
sub_6:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.7024 - F1: 0.6989
sub_12:Test (Best Model) - Loss: 0.3377 - Accuracy: 0.8452 - F1: 0.8425
sub_14:Test (Best Model) - Loss: 0.8646 - Accuracy: 0.6071 - F1: 0.5619
sub_13:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.6190 - F1: 0.6156
sub_4:Test (Best Model) - Loss: 0.4501 - Accuracy: 0.8214 - F1: 0.8183
sub_10:Test (Best Model) - Loss: 0.3745 - Accuracy: 0.8571 - F1: 0.8558
sub_1:Test (Best Model) - Loss: 0.3723 - Accuracy: 0.8929 - F1: 0.8921
sub_9:Test (Best Model) - Loss: 0.4434 - Accuracy: 0.7738 - F1: 0.7641
sub_3:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.7024 - F1: 0.6825
sub_6:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.7024 - F1: 0.6863
sub_11:Test (Best Model) - Loss: 0.3151 - Accuracy: 0.9286 - F1: 0.9286
sub_2:Test (Best Model) - Loss: 0.4253 - Accuracy: 0.7738 - F1: 0.7664
sub_8:Test (Best Model) - Loss: 0.3626 - Accuracy: 0.8452 - F1: 0.8434
sub_13:Test (Best Model) - Loss: 0.2779 - Accuracy: 0.9167 - F1: 0.9161
sub_12:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.4818 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 0.5633 - Accuracy: 0.7024 - F1: 0.7013
sub_9:Test (Best Model) - Loss: 0.5577 - Accuracy: 0.7500 - F1: 0.7418
sub_4:Test (Best Model) - Loss: 0.4596 - Accuracy: 0.7976 - F1: 0.7941
sub_3:Test (Best Model) - Loss: 0.6394 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 1.0767 - Accuracy: 0.5238 - F1: 0.3842
sub_11:Test (Best Model) - Loss: 0.2136 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.3561 - Accuracy: 0.8690 - F1: 0.8681
sub_10:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 0.3851 - Accuracy: 0.8452 - F1: 0.8450
sub_2:Test (Best Model) - Loss: 0.4301 - Accuracy: 0.8690 - F1: 0.8686
sub_4:Test (Best Model) - Loss: 0.4357 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.4774 - Accuracy: 0.7619 - F1: 0.7551
sub_14:Test (Best Model) - Loss: 0.7874 - Accuracy: 0.6190 - F1: 0.5634
sub_12:Test (Best Model) - Loss: 0.3932 - Accuracy: 0.8333 - F1: 0.8309
sub_2:Test (Best Model) - Loss: 0.1601 - Accuracy: 0.9405 - F1: 0.9405
sub_4:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.7500 - F1: 0.7471
sub_10:Test (Best Model) - Loss: 0.4002 - Accuracy: 0.8452 - F1: 0.8447
sub_12:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5357 - F1: 0.4081
sub_8:Test (Best Model) - Loss: 0.5180 - Accuracy: 0.7500 - F1: 0.7500
sub_8:Test (Best Model) - Loss: 0.2505 - Accuracy: 0.9405 - F1: 0.9405
sub_4:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 0.4520 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.5673 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.3339 - Accuracy: 0.8571 - F1: 0.8571
sub_2:Test (Best Model) - Loss: 0.3656 - Accuracy: 0.8452 - F1: 0.8414
sub_12:Test (Best Model) - Loss: 0.5191 - Accuracy: 0.7738 - F1: 0.7722
sub_12:Test (Best Model) - Loss: 0.4652 - Accuracy: 0.8095 - F1: 0.8091

=== Summary Results ===

acc: 74.24 ± 8.66
F1: 72.23 ± 9.88
acc-in: 82.60 ± 9.56
F1-in: 81.16 ± 10.67
