lr: 0.0001
sub_13:Test (Best Model) - Loss: 1.4825 - Accuracy: 0.3762 - F1: 0.3000
sub_8:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.4333 - F1: 0.4098
sub_10:Test (Best Model) - Loss: 1.4474 - Accuracy: 0.4095 - F1: 0.3282
sub_12:Test (Best Model) - Loss: 1.4303 - Accuracy: 0.4476 - F1: 0.4026
sub_7:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.3048 - F1: 0.2729
sub_1:Test (Best Model) - Loss: 1.4501 - Accuracy: 0.4190 - F1: 0.3117
sub_4:Test (Best Model) - Loss: 1.3654 - Accuracy: 0.4571 - F1: 0.3737
sub_11:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.4762 - F1: 0.4189
sub_5:Test (Best Model) - Loss: 1.5623 - Accuracy: 0.2905 - F1: 0.2099
sub_6:Test (Best Model) - Loss: 1.4590 - Accuracy: 0.3905 - F1: 0.2728
sub_3:Test (Best Model) - Loss: 1.5752 - Accuracy: 0.2857 - F1: 0.1705
sub_9:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.4333 - F1: 0.4020
sub_13:Test (Best Model) - Loss: 1.4647 - Accuracy: 0.3381 - F1: 0.2642
sub_2:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.4095 - F1: 0.3419
sub_8:Test (Best Model) - Loss: 1.3243 - Accuracy: 0.5238 - F1: 0.5206
sub_14:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.4476 - F1: 0.4419
sub_10:Test (Best Model) - Loss: 1.4412 - Accuracy: 0.4333 - F1: 0.3847
sub_12:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.4286 - F1: 0.4094
sub_1:Test (Best Model) - Loss: 1.4845 - Accuracy: 0.3905 - F1: 0.2921
sub_5:Test (Best Model) - Loss: 1.5204 - Accuracy: 0.3381 - F1: 0.2480
sub_2:Test (Best Model) - Loss: 1.4339 - Accuracy: 0.4095 - F1: 0.2915
sub_4:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.4571 - F1: 0.3906
sub_8:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.4810 - F1: 0.4681
sub_13:Test (Best Model) - Loss: 1.4990 - Accuracy: 0.3429 - F1: 0.2685
sub_3:Test (Best Model) - Loss: 1.5625 - Accuracy: 0.2762 - F1: 0.1769
sub_6:Test (Best Model) - Loss: 1.5134 - Accuracy: 0.3905 - F1: 0.2942
sub_11:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.5190 - F1: 0.4926
sub_7:Test (Best Model) - Loss: 1.5830 - Accuracy: 0.2524 - F1: 0.2027
sub_5:Test (Best Model) - Loss: 1.5208 - Accuracy: 0.3381 - F1: 0.2486
sub_8:Test (Best Model) - Loss: 1.4136 - Accuracy: 0.5095 - F1: 0.4951
sub_2:Test (Best Model) - Loss: 1.4280 - Accuracy: 0.4190 - F1: 0.3390
sub_10:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.4476 - F1: 0.3930
sub_4:Test (Best Model) - Loss: 1.4463 - Accuracy: 0.4476 - F1: 0.4032
sub_9:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.4619 - F1: 0.4332
sub_14:Test (Best Model) - Loss: 1.2870 - Accuracy: 0.5000 - F1: 0.4816
sub_12:Test (Best Model) - Loss: 1.4194 - Accuracy: 0.4238 - F1: 0.3651
sub_8:Test (Best Model) - Loss: 1.3999 - Accuracy: 0.4000 - F1: 0.3677
sub_1:Test (Best Model) - Loss: 1.4604 - Accuracy: 0.4000 - F1: 0.2899
sub_3:Test (Best Model) - Loss: 1.5027 - Accuracy: 0.3381 - F1: 0.2754
sub_6:Test (Best Model) - Loss: 1.4555 - Accuracy: 0.3714 - F1: 0.3042
sub_7:Test (Best Model) - Loss: 1.5520 - Accuracy: 0.3000 - F1: 0.2537
sub_4:Test (Best Model) - Loss: 1.4242 - Accuracy: 0.4524 - F1: 0.4078
sub_2:Test (Best Model) - Loss: 1.4401 - Accuracy: 0.3952 - F1: 0.3096
sub_13:Test (Best Model) - Loss: 1.4939 - Accuracy: 0.3048 - F1: 0.2214
sub_11:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.4762 - F1: 0.4453
sub_5:Test (Best Model) - Loss: 1.5753 - Accuracy: 0.2667 - F1: 0.1730
sub_12:Test (Best Model) - Loss: 1.4303 - Accuracy: 0.4429 - F1: 0.4246
sub_8:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.4762 - F1: 0.4741
sub_14:Test (Best Model) - Loss: 1.3120 - Accuracy: 0.4905 - F1: 0.4601
sub_9:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.4429 - F1: 0.3836
sub_4:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.4000 - F1: 0.3379
sub_10:Test (Best Model) - Loss: 1.3437 - Accuracy: 0.4381 - F1: 0.4003
sub_6:Test (Best Model) - Loss: 1.4942 - Accuracy: 0.3429 - F1: 0.2867
sub_3:Test (Best Model) - Loss: 1.5652 - Accuracy: 0.2857 - F1: 0.1794
sub_7:Test (Best Model) - Loss: 1.5354 - Accuracy: 0.3048 - F1: 0.2432
sub_12:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.5048 - F1: 0.4890
sub_13:Test (Best Model) - Loss: 1.4924 - Accuracy: 0.3143 - F1: 0.2084
sub_5:Test (Best Model) - Loss: 1.5468 - Accuracy: 0.3238 - F1: 0.2500
sub_2:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.4048 - F1: 0.3408
sub_11:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.5143 - F1: 0.4729
sub_8:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.5000 - F1: 0.4995
sub_14:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.4857 - F1: 0.4522
sub_1:Test (Best Model) - Loss: 1.4538 - Accuracy: 0.3857 - F1: 0.2809
sub_4:Test (Best Model) - Loss: 1.3465 - Accuracy: 0.4762 - F1: 0.4462
sub_3:Test (Best Model) - Loss: 1.5825 - Accuracy: 0.2381 - F1: 0.1196
sub_6:Test (Best Model) - Loss: 1.4266 - Accuracy: 0.4000 - F1: 0.3274
sub_12:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.4190 - F1: 0.3537
sub_10:Test (Best Model) - Loss: 1.4070 - Accuracy: 0.4190 - F1: 0.3624
sub_11:Test (Best Model) - Loss: 1.4560 - Accuracy: 0.4238 - F1: 0.3530
sub_8:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.4952 - F1: 0.4631
sub_13:Test (Best Model) - Loss: 1.4612 - Accuracy: 0.4143 - F1: 0.4071
sub_7:Test (Best Model) - Loss: 1.5293 - Accuracy: 0.3048 - F1: 0.2736
sub_2:Test (Best Model) - Loss: 1.4064 - Accuracy: 0.4762 - F1: 0.4413
sub_14:Test (Best Model) - Loss: 1.4088 - Accuracy: 0.4667 - F1: 0.4414
sub_5:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.4762 - F1: 0.4331
sub_10:Test (Best Model) - Loss: 1.4423 - Accuracy: 0.4667 - F1: 0.4490
sub_9:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.4143 - F1: 0.3342
sub_4:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.4238 - F1: 0.4081
sub_3:Test (Best Model) - Loss: 1.4409 - Accuracy: 0.4095 - F1: 0.3611
sub_8:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.4857 - F1: 0.4432
sub_6:Test (Best Model) - Loss: 1.4350 - Accuracy: 0.3762 - F1: 0.3569
sub_12:Test (Best Model) - Loss: 1.4734 - Accuracy: 0.3714 - F1: 0.3041
sub_8:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.5238 - F1: 0.4895
sub_1:Test (Best Model) - Loss: 1.4348 - Accuracy: 0.3857 - F1: 0.2832
sub_4:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.4952 - F1: 0.4907
sub_2:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.4095 - F1: 0.4004
sub_7:Test (Best Model) - Loss: 1.4400 - Accuracy: 0.4238 - F1: 0.3713
sub_13:Test (Best Model) - Loss: 1.4904 - Accuracy: 0.3857 - F1: 0.3393
sub_11:Test (Best Model) - Loss: 1.2901 - Accuracy: 0.5000 - F1: 0.4797
sub_5:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.4333 - F1: 0.3825
sub_3:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.4333 - F1: 0.4234
sub_10:Test (Best Model) - Loss: 1.3268 - Accuracy: 0.4810 - F1: 0.4732
sub_14:Test (Best Model) - Loss: 1.2815 - Accuracy: 0.5619 - F1: 0.5347
sub_12:Test (Best Model) - Loss: 1.4872 - Accuracy: 0.3333 - F1: 0.2736
sub_8:Test (Best Model) - Loss: 1.4135 - Accuracy: 0.4429 - F1: 0.4357
sub_2:Test (Best Model) - Loss: 1.3492 - Accuracy: 0.5286 - F1: 0.5122
sub_3:Test (Best Model) - Loss: 1.4606 - Accuracy: 0.3238 - F1: 0.2972
sub_9:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.4619 - F1: 0.4373
sub_4:Test (Best Model) - Loss: 1.3182 - Accuracy: 0.4190 - F1: 0.4120
sub_1:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3714 - F1: 0.3435
sub_8:Test (Best Model) - Loss: 1.4365 - Accuracy: 0.4571 - F1: 0.4244
sub_10:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.4810 - F1: 0.4496
sub_13:Test (Best Model) - Loss: 1.4241 - Accuracy: 0.3905 - F1: 0.3420
sub_5:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.4714 - F1: 0.4227
sub_11:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.5048 - F1: 0.4848
sub_6:Test (Best Model) - Loss: 1.5355 - Accuracy: 0.3476 - F1: 0.3421
sub_7:Test (Best Model) - Loss: 1.4750 - Accuracy: 0.3762 - F1: 0.3335
sub_14:Test (Best Model) - Loss: 1.1514 - Accuracy: 0.6429 - F1: 0.6277
sub_12:Test (Best Model) - Loss: 1.4731 - Accuracy: 0.3524 - F1: 0.2979
sub_11:Test (Best Model) - Loss: 1.4058 - Accuracy: 0.4571 - F1: 0.4051
sub_4:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.4190 - F1: 0.3899
sub_6:Test (Best Model) - Loss: 1.4983 - Accuracy: 0.4095 - F1: 0.4090
sub_9:Test (Best Model) - Loss: 1.4789 - Accuracy: 0.3381 - F1: 0.2529
sub_2:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.4905 - F1: 0.4500
sub_10:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.4381 - F1: 0.4136
sub_3:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.3667 - F1: 0.2984
sub_5:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.4762 - F1: 0.4220
sub_12:Test (Best Model) - Loss: 1.4592 - Accuracy: 0.3381 - F1: 0.2813
sub_7:Test (Best Model) - Loss: 1.4700 - Accuracy: 0.3476 - F1: 0.3030
sub_1:Test (Best Model) - Loss: 1.4399 - Accuracy: 0.3905 - F1: 0.3222
sub_9:Test (Best Model) - Loss: 1.4419 - Accuracy: 0.4190 - F1: 0.3736
sub_2:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.4524 - F1: 0.4176
sub_8:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.4714 - F1: 0.4298
sub_6:Test (Best Model) - Loss: 1.4455 - Accuracy: 0.3952 - F1: 0.3888
sub_11:Test (Best Model) - Loss: 1.3217 - Accuracy: 0.4714 - F1: 0.3994
sub_4:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.4714 - F1: 0.4077
sub_3:Test (Best Model) - Loss: 1.4379 - Accuracy: 0.3667 - F1: 0.3436
sub_2:Test (Best Model) - Loss: 1.4663 - Accuracy: 0.3619 - F1: 0.3720
sub_14:Test (Best Model) - Loss: 1.2053 - Accuracy: 0.5429 - F1: 0.4983
sub_13:Test (Best Model) - Loss: 1.4631 - Accuracy: 0.3714 - F1: 0.3096
sub_12:Test (Best Model) - Loss: 1.4693 - Accuracy: 0.3905 - F1: 0.3176
sub_9:Test (Best Model) - Loss: 1.4910 - Accuracy: 0.3571 - F1: 0.2834
sub_10:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.4190 - F1: 0.4068
sub_4:Test (Best Model) - Loss: 1.4225 - Accuracy: 0.4857 - F1: 0.4551
sub_8:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.4810 - F1: 0.4487
sub_11:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.4762 - F1: 0.4474
sub_5:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.4952 - F1: 0.3930
sub_7:Test (Best Model) - Loss: 1.5051 - Accuracy: 0.3619 - F1: 0.2794
sub_3:Test (Best Model) - Loss: 1.5288 - Accuracy: 0.3000 - F1: 0.2814
sub_8:Test (Best Model) - Loss: 1.4101 - Accuracy: 0.4333 - F1: 0.4233
sub_2:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.4190 - F1: 0.4275
sub_6:Test (Best Model) - Loss: 1.4175 - Accuracy: 0.4143 - F1: 0.4006
sub_13:Test (Best Model) - Loss: 1.4167 - Accuracy: 0.4095 - F1: 0.3425
sub_9:Test (Best Model) - Loss: 1.4679 - Accuracy: 0.3810 - F1: 0.2884
sub_10:Test (Best Model) - Loss: 1.5319 - Accuracy: 0.3381 - F1: 0.2948
sub_14:Test (Best Model) - Loss: 1.2445 - Accuracy: 0.5429 - F1: 0.5078
sub_12:Test (Best Model) - Loss: 1.4490 - Accuracy: 0.3762 - F1: 0.2970
sub_1:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.4333 - F1: 0.4412
sub_4:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.4619 - F1: 0.4118
sub_11:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.4571 - F1: 0.4273
sub_2:Test (Best Model) - Loss: 1.4315 - Accuracy: 0.4714 - F1: 0.4715
sub_3:Test (Best Model) - Loss: 1.4952 - Accuracy: 0.3000 - F1: 0.2934
sub_6:Test (Best Model) - Loss: 1.4400 - Accuracy: 0.4381 - F1: 0.4117
sub_4:Test (Best Model) - Loss: 1.4539 - Accuracy: 0.4143 - F1: 0.3613
sub_9:Test (Best Model) - Loss: 1.4566 - Accuracy: 0.3429 - F1: 0.2740
sub_13:Test (Best Model) - Loss: 1.4684 - Accuracy: 0.4190 - F1: 0.3117
sub_14:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.5381 - F1: 0.4975
sub_1:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.4238 - F1: 0.4206
sub_12:Test (Best Model) - Loss: 1.4520 - Accuracy: 0.3905 - F1: 0.3264
sub_2:Test (Best Model) - Loss: 1.3716 - Accuracy: 0.4714 - F1: 0.4697
sub_10:Test (Best Model) - Loss: 1.5046 - Accuracy: 0.3619 - F1: 0.3213
sub_3:Test (Best Model) - Loss: 1.5217 - Accuracy: 0.3095 - F1: 0.2653
sub_5:Test (Best Model) - Loss: 1.4568 - Accuracy: 0.2905 - F1: 0.3023
sub_7:Test (Best Model) - Loss: 1.5554 - Accuracy: 0.3333 - F1: 0.2574
sub_12:Test (Best Model) - Loss: 1.4646 - Accuracy: 0.3714 - F1: 0.2899
sub_10:Test (Best Model) - Loss: 1.5435 - Accuracy: 0.3190 - F1: 0.2595
sub_6:Test (Best Model) - Loss: 1.4067 - Accuracy: 0.4190 - F1: 0.3786
sub_11:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.4476 - F1: 0.4283
sub_4:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.4571 - F1: 0.4147
sub_2:Test (Best Model) - Loss: 1.4146 - Accuracy: 0.4619 - F1: 0.4484
sub_1:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.4381 - F1: 0.4188
sub_14:Test (Best Model) - Loss: 1.5678 - Accuracy: 0.2857 - F1: 0.2166
sub_9:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.3810 - F1: 0.3721
sub_13:Test (Best Model) - Loss: 1.4347 - Accuracy: 0.4286 - F1: 0.3416
sub_5:Test (Best Model) - Loss: 1.4286 - Accuracy: 0.3667 - F1: 0.3689
sub_12:Test (Best Model) - Loss: 1.4601 - Accuracy: 0.4143 - F1: 0.3686
sub_14:Test (Best Model) - Loss: 1.5713 - Accuracy: 0.2905 - F1: 0.2250
sub_10:Test (Best Model) - Loss: 1.4833 - Accuracy: 0.3333 - F1: 0.2839
sub_6:Test (Best Model) - Loss: 1.4078 - Accuracy: 0.4238 - F1: 0.3949
sub_11:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.4190 - F1: 0.4030
sub_13:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.4952 - F1: 0.4313
sub_3:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.3476 - F1: 0.2889
sub_7:Test (Best Model) - Loss: 1.5897 - Accuracy: 0.2571 - F1: 0.2301
sub_1:Test (Best Model) - Loss: 1.3036 - Accuracy: 0.5048 - F1: 0.5090
sub_5:Test (Best Model) - Loss: 1.4536 - Accuracy: 0.4143 - F1: 0.4044
sub_14:Test (Best Model) - Loss: 1.5714 - Accuracy: 0.2762 - F1: 0.2032
sub_9:Test (Best Model) - Loss: 1.4474 - Accuracy: 0.4190 - F1: 0.3614
sub_3:Test (Best Model) - Loss: 1.5323 - Accuracy: 0.3381 - F1: 0.3291
sub_10:Test (Best Model) - Loss: 1.5170 - Accuracy: 0.3714 - F1: 0.3240
sub_11:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.4762 - F1: 0.4389
sub_6:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.4143 - F1: 0.4010
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.5048 - F1: 0.4926
sub_14:Test (Best Model) - Loss: 1.5890 - Accuracy: 0.2476 - F1: 0.1617
sub_9:Test (Best Model) - Loss: 1.4463 - Accuracy: 0.4286 - F1: 0.3734
sub_13:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.4381 - F1: 0.3615
sub_5:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.4524 - F1: 0.4498
sub_14:Test (Best Model) - Loss: 1.5877 - Accuracy: 0.2571 - F1: 0.1681
sub_7:Test (Best Model) - Loss: 1.4998 - Accuracy: 0.3619 - F1: 0.2993
sub_9:Test (Best Model) - Loss: 1.4240 - Accuracy: 0.4429 - F1: 0.4031
sub_1:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.4429 - F1: 0.4282
sub_6:Test (Best Model) - Loss: 1.4229 - Accuracy: 0.4381 - F1: 0.4171
sub_13:Test (Best Model) - Loss: 1.4357 - Accuracy: 0.4429 - F1: 0.3571
sub_5:Test (Best Model) - Loss: 1.4564 - Accuracy: 0.4048 - F1: 0.4052
sub_11:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.4476 - F1: 0.4308
sub_7:Test (Best Model) - Loss: 1.4977 - Accuracy: 0.3333 - F1: 0.3331
sub_9:Test (Best Model) - Loss: 1.4356 - Accuracy: 0.4381 - F1: 0.4022
sub_1:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.4762 - F1: 0.4265
sub_7:Test (Best Model) - Loss: 1.4613 - Accuracy: 0.3667 - F1: 0.3201
sub_1:Test (Best Model) - Loss: 1.4595 - Accuracy: 0.4381 - F1: 0.4304
sub_7:Test (Best Model) - Loss: 1.5249 - Accuracy: 0.2810 - F1: 0.2382

=== Summary Results ===

acc: 41.10 ± 4.30
F1: 36.58 ± 5.03
acc-in: 51.22 ± 3.95
F1-in: 48.90 ± 3.83
