lr: 0.001
sub_6:Test (Best Model) - Loss: 1.7394 - Accuracy: 0.3905 - F1: 0.3876
sub_9:Test (Best Model) - Loss: 1.9994 - Accuracy: 0.3857 - F1: 0.3330
sub_5:Test (Best Model) - Loss: 1.8203 - Accuracy: 0.4000 - F1: 0.3655
sub_14:Test (Best Model) - Loss: 1.8109 - Accuracy: 0.4095 - F1: 0.4194
sub_13:Test (Best Model) - Loss: 1.9818 - Accuracy: 0.4095 - F1: 0.3749
sub_11:Test (Best Model) - Loss: 2.0438 - Accuracy: 0.4048 - F1: 0.3820
sub_3:Test (Best Model) - Loss: 2.2368 - Accuracy: 0.3619 - F1: 0.3247
sub_7:Test (Best Model) - Loss: 2.2970 - Accuracy: 0.3095 - F1: 0.3150
sub_12:Test (Best Model) - Loss: 2.2858 - Accuracy: 0.3857 - F1: 0.3824
sub_10:Test (Best Model) - Loss: 2.1140 - Accuracy: 0.3667 - F1: 0.3422
sub_4:Test (Best Model) - Loss: 2.0112 - Accuracy: 0.3429 - F1: 0.3482
sub_8:Test (Best Model) - Loss: 1.8108 - Accuracy: 0.4429 - F1: 0.4399
sub_2:Test (Best Model) - Loss: 1.8148 - Accuracy: 0.4667 - F1: 0.4589
sub_1:Test (Best Model) - Loss: 2.3166 - Accuracy: 0.3667 - F1: 0.3325
sub_6:Test (Best Model) - Loss: 2.1604 - Accuracy: 0.3429 - F1: 0.3359
sub_9:Test (Best Model) - Loss: 1.8189 - Accuracy: 0.3952 - F1: 0.3465
sub_5:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.3952 - F1: 0.3702
sub_13:Test (Best Model) - Loss: 1.8024 - Accuracy: 0.3571 - F1: 0.3467
sub_14:Test (Best Model) - Loss: 2.0244 - Accuracy: 0.3905 - F1: 0.3996
sub_3:Test (Best Model) - Loss: 2.4902 - Accuracy: 0.3190 - F1: 0.2749
sub_12:Test (Best Model) - Loss: 1.7626 - Accuracy: 0.4095 - F1: 0.4116
sub_7:Test (Best Model) - Loss: 2.2096 - Accuracy: 0.3000 - F1: 0.2971
sub_11:Test (Best Model) - Loss: 1.8268 - Accuracy: 0.4238 - F1: 0.4176
sub_8:Test (Best Model) - Loss: 1.7846 - Accuracy: 0.4190 - F1: 0.4088
sub_2:Test (Best Model) - Loss: 1.5143 - Accuracy: 0.5000 - F1: 0.4801
sub_10:Test (Best Model) - Loss: 2.2864 - Accuracy: 0.4095 - F1: 0.3921
sub_4:Test (Best Model) - Loss: 2.4265 - Accuracy: 0.3619 - F1: 0.3627
sub_6:Test (Best Model) - Loss: 2.0371 - Accuracy: 0.3619 - F1: 0.3536
sub_1:Test (Best Model) - Loss: 1.9370 - Accuracy: 0.4143 - F1: 0.3832
sub_9:Test (Best Model) - Loss: 1.9246 - Accuracy: 0.4095 - F1: 0.3967
sub_13:Test (Best Model) - Loss: 1.9936 - Accuracy: 0.3857 - F1: 0.3594
sub_14:Test (Best Model) - Loss: 1.6918 - Accuracy: 0.3810 - F1: 0.3656
sub_12:Test (Best Model) - Loss: 2.2115 - Accuracy: 0.3905 - F1: 0.3721
sub_7:Test (Best Model) - Loss: 2.0357 - Accuracy: 0.3286 - F1: 0.3162
sub_5:Test (Best Model) - Loss: 1.9621 - Accuracy: 0.3952 - F1: 0.3710
sub_4:Test (Best Model) - Loss: 1.9445 - Accuracy: 0.3714 - F1: 0.3664
sub_2:Test (Best Model) - Loss: 1.7297 - Accuracy: 0.4381 - F1: 0.4204
sub_14:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.4095 - F1: 0.3871
sub_10:Test (Best Model) - Loss: 2.2546 - Accuracy: 0.3952 - F1: 0.3568
sub_3:Test (Best Model) - Loss: 2.4799 - Accuracy: 0.3429 - F1: 0.3153
sub_8:Test (Best Model) - Loss: 1.6378 - Accuracy: 0.5095 - F1: 0.4982
sub_13:Test (Best Model) - Loss: 1.7824 - Accuracy: 0.3667 - F1: 0.3502
sub_7:Test (Best Model) - Loss: 2.0387 - Accuracy: 0.3619 - F1: 0.3486
sub_11:Test (Best Model) - Loss: 2.0735 - Accuracy: 0.4000 - F1: 0.3748
sub_12:Test (Best Model) - Loss: 2.2614 - Accuracy: 0.3905 - F1: 0.3731
sub_9:Test (Best Model) - Loss: 1.9014 - Accuracy: 0.4381 - F1: 0.4065
sub_1:Test (Best Model) - Loss: 2.4061 - Accuracy: 0.4143 - F1: 0.3875
sub_6:Test (Best Model) - Loss: 2.1443 - Accuracy: 0.3476 - F1: 0.3343
sub_5:Test (Best Model) - Loss: 1.6980 - Accuracy: 0.4095 - F1: 0.3838
sub_8:Test (Best Model) - Loss: 1.5416 - Accuracy: 0.4190 - F1: 0.4211
sub_2:Test (Best Model) - Loss: 1.6961 - Accuracy: 0.4619 - F1: 0.4458
sub_4:Test (Best Model) - Loss: 2.0130 - Accuracy: 0.3619 - F1: 0.3581
sub_13:Test (Best Model) - Loss: 1.7502 - Accuracy: 0.3857 - F1: 0.3696
sub_14:Test (Best Model) - Loss: 1.8496 - Accuracy: 0.3905 - F1: 0.3995
sub_12:Test (Best Model) - Loss: 1.6984 - Accuracy: 0.3714 - F1: 0.3380
sub_10:Test (Best Model) - Loss: 2.3510 - Accuracy: 0.3619 - F1: 0.3347
sub_7:Test (Best Model) - Loss: 2.3421 - Accuracy: 0.3238 - F1: 0.3117
sub_8:Test (Best Model) - Loss: 1.4947 - Accuracy: 0.4333 - F1: 0.4155
sub_11:Test (Best Model) - Loss: 2.1745 - Accuracy: 0.4095 - F1: 0.3871
sub_5:Test (Best Model) - Loss: 1.4966 - Accuracy: 0.4476 - F1: 0.4143
sub_2:Test (Best Model) - Loss: 1.4944 - Accuracy: 0.4571 - F1: 0.4463
sub_6:Test (Best Model) - Loss: 1.9846 - Accuracy: 0.3333 - F1: 0.3141
sub_12:Test (Best Model) - Loss: 1.8404 - Accuracy: 0.3762 - F1: 0.3828
sub_10:Test (Best Model) - Loss: 1.6873 - Accuracy: 0.4095 - F1: 0.3948
sub_14:Test (Best Model) - Loss: 1.5553 - Accuracy: 0.4762 - F1: 0.4687
sub_4:Test (Best Model) - Loss: 1.8532 - Accuracy: 0.3667 - F1: 0.3541
sub_9:Test (Best Model) - Loss: 2.4138 - Accuracy: 0.3952 - F1: 0.3595
sub_1:Test (Best Model) - Loss: 2.3373 - Accuracy: 0.3952 - F1: 0.3747
sub_13:Test (Best Model) - Loss: 2.0752 - Accuracy: 0.3571 - F1: 0.3398
sub_3:Test (Best Model) - Loss: 2.1464 - Accuracy: 0.3762 - F1: 0.3342
sub_8:Test (Best Model) - Loss: 1.9242 - Accuracy: 0.4429 - F1: 0.4493
sub_11:Test (Best Model) - Loss: 1.6541 - Accuracy: 0.4190 - F1: 0.3986
sub_2:Test (Best Model) - Loss: 1.9968 - Accuracy: 0.4524 - F1: 0.4574
sub_14:Test (Best Model) - Loss: 1.6876 - Accuracy: 0.5143 - F1: 0.4994
sub_7:Test (Best Model) - Loss: 2.2818 - Accuracy: 0.3476 - F1: 0.3256
sub_4:Test (Best Model) - Loss: 1.9559 - Accuracy: 0.3619 - F1: 0.3679
sub_12:Test (Best Model) - Loss: 2.2965 - Accuracy: 0.3381 - F1: 0.3322
sub_6:Test (Best Model) - Loss: 2.4399 - Accuracy: 0.3190 - F1: 0.3057
sub_9:Test (Best Model) - Loss: 1.8521 - Accuracy: 0.4143 - F1: 0.3850
sub_1:Test (Best Model) - Loss: 1.7181 - Accuracy: 0.4000 - F1: 0.3755
sub_14:Test (Best Model) - Loss: 1.6457 - Accuracy: 0.5048 - F1: 0.4955
sub_3:Test (Best Model) - Loss: 2.0001 - Accuracy: 0.3381 - F1: 0.2741
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.3952 - F1: 0.3889
sub_8:Test (Best Model) - Loss: 1.7769 - Accuracy: 0.4524 - F1: 0.4520
sub_6:Test (Best Model) - Loss: 2.1034 - Accuracy: 0.3429 - F1: 0.3271
sub_2:Test (Best Model) - Loss: 1.8022 - Accuracy: 0.4810 - F1: 0.4858
sub_10:Test (Best Model) - Loss: 2.6325 - Accuracy: 0.3667 - F1: 0.3441
sub_12:Test (Best Model) - Loss: 2.5164 - Accuracy: 0.3571 - F1: 0.3583
sub_5:Test (Best Model) - Loss: 2.2065 - Accuracy: 0.4333 - F1: 0.4263
sub_14:Test (Best Model) - Loss: 1.4404 - Accuracy: 0.4952 - F1: 0.4889
sub_9:Test (Best Model) - Loss: 2.0185 - Accuracy: 0.4095 - F1: 0.3854
sub_7:Test (Best Model) - Loss: 2.1518 - Accuracy: 0.3619 - F1: 0.3425
sub_4:Test (Best Model) - Loss: 2.6211 - Accuracy: 0.3667 - F1: 0.3553
sub_13:Test (Best Model) - Loss: 2.4130 - Accuracy: 0.3048 - F1: 0.2529
sub_8:Test (Best Model) - Loss: 1.8205 - Accuracy: 0.4190 - F1: 0.4250
sub_10:Test (Best Model) - Loss: 1.7812 - Accuracy: 0.3667 - F1: 0.3428
sub_3:Test (Best Model) - Loss: 1.4632 - Accuracy: 0.4095 - F1: 0.3973
sub_12:Test (Best Model) - Loss: 1.9758 - Accuracy: 0.3810 - F1: 0.3840
sub_14:Test (Best Model) - Loss: 1.3086 - Accuracy: 0.5048 - F1: 0.4844
sub_2:Test (Best Model) - Loss: 1.7559 - Accuracy: 0.4238 - F1: 0.4403
sub_6:Test (Best Model) - Loss: 2.8150 - Accuracy: 0.3524 - F1: 0.3554
sub_4:Test (Best Model) - Loss: 2.2126 - Accuracy: 0.3333 - F1: 0.3263
sub_1:Test (Best Model) - Loss: 1.7584 - Accuracy: 0.4381 - F1: 0.4373
sub_9:Test (Best Model) - Loss: 1.8563 - Accuracy: 0.4095 - F1: 0.3904
sub_7:Test (Best Model) - Loss: 2.0141 - Accuracy: 0.3857 - F1: 0.3696
sub_5:Test (Best Model) - Loss: 1.9040 - Accuracy: 0.4381 - F1: 0.4281
sub_10:Test (Best Model) - Loss: 2.1371 - Accuracy: 0.3762 - F1: 0.3578
sub_3:Test (Best Model) - Loss: 2.1433 - Accuracy: 0.3952 - F1: 0.3899
sub_6:Test (Best Model) - Loss: 2.1353 - Accuracy: 0.3095 - F1: 0.2873
sub_13:Test (Best Model) - Loss: 2.3777 - Accuracy: 0.3571 - F1: 0.3085
sub_8:Test (Best Model) - Loss: 1.9455 - Accuracy: 0.4286 - F1: 0.4337
sub_11:Test (Best Model) - Loss: 1.9892 - Accuracy: 0.3619 - F1: 0.3636
sub_14:Test (Best Model) - Loss: 2.4072 - Accuracy: 0.4333 - F1: 0.3984
sub_4:Test (Best Model) - Loss: 1.9401 - Accuracy: 0.4190 - F1: 0.4146
sub_9:Test (Best Model) - Loss: 1.5518 - Accuracy: 0.4429 - F1: 0.4044
sub_2:Test (Best Model) - Loss: 1.8443 - Accuracy: 0.3952 - F1: 0.4071
sub_12:Test (Best Model) - Loss: 2.9513 - Accuracy: 0.3238 - F1: 0.3178
sub_7:Test (Best Model) - Loss: 1.9102 - Accuracy: 0.3810 - F1: 0.3673
sub_1:Test (Best Model) - Loss: 2.0286 - Accuracy: 0.4476 - F1: 0.4553
sub_6:Test (Best Model) - Loss: 1.9216 - Accuracy: 0.3619 - F1: 0.3449
sub_8:Test (Best Model) - Loss: 1.9578 - Accuracy: 0.4000 - F1: 0.4059
sub_13:Test (Best Model) - Loss: 2.1763 - Accuracy: 0.3333 - F1: 0.2981
sub_3:Test (Best Model) - Loss: 2.2045 - Accuracy: 0.3810 - F1: 0.3799
sub_9:Test (Best Model) - Loss: 1.6382 - Accuracy: 0.4000 - F1: 0.3637
sub_10:Test (Best Model) - Loss: 2.6888 - Accuracy: 0.3667 - F1: 0.3407
sub_4:Test (Best Model) - Loss: 1.8521 - Accuracy: 0.3762 - F1: 0.3666
sub_12:Test (Best Model) - Loss: 1.9517 - Accuracy: 0.3190 - F1: 0.3277
sub_11:Test (Best Model) - Loss: 2.1849 - Accuracy: 0.3571 - F1: 0.3494
sub_5:Test (Best Model) - Loss: 2.5637 - Accuracy: 0.3619 - F1: 0.3428
sub_14:Test (Best Model) - Loss: 1.8541 - Accuracy: 0.4619 - F1: 0.4171
sub_2:Test (Best Model) - Loss: 1.9073 - Accuracy: 0.4238 - F1: 0.4399
sub_6:Test (Best Model) - Loss: 1.9954 - Accuracy: 0.4143 - F1: 0.4071
sub_8:Test (Best Model) - Loss: 1.6996 - Accuracy: 0.4143 - F1: 0.3619
sub_7:Test (Best Model) - Loss: 2.0399 - Accuracy: 0.3952 - F1: 0.3683
sub_3:Test (Best Model) - Loss: 1.8086 - Accuracy: 0.3810 - F1: 0.3889
sub_9:Test (Best Model) - Loss: 1.7852 - Accuracy: 0.3333 - F1: 0.3144
sub_1:Test (Best Model) - Loss: 2.0693 - Accuracy: 0.4619 - F1: 0.4728
sub_4:Test (Best Model) - Loss: 2.1182 - Accuracy: 0.3476 - F1: 0.3533
sub_12:Test (Best Model) - Loss: 1.8409 - Accuracy: 0.3000 - F1: 0.3045
sub_14:Test (Best Model) - Loss: 1.8665 - Accuracy: 0.3762 - F1: 0.3539
sub_5:Test (Best Model) - Loss: 1.8826 - Accuracy: 0.3952 - F1: 0.3868
sub_13:Test (Best Model) - Loss: 2.5996 - Accuracy: 0.3333 - F1: 0.2963
sub_8:Test (Best Model) - Loss: 1.9175 - Accuracy: 0.4286 - F1: 0.3831
sub_10:Test (Best Model) - Loss: 2.2896 - Accuracy: 0.4143 - F1: 0.4138
sub_9:Test (Best Model) - Loss: 1.9922 - Accuracy: 0.3667 - F1: 0.3492
sub_2:Test (Best Model) - Loss: 1.8883 - Accuracy: 0.4476 - F1: 0.4276
sub_11:Test (Best Model) - Loss: 2.1859 - Accuracy: 0.4143 - F1: 0.3963
sub_3:Test (Best Model) - Loss: 2.0514 - Accuracy: 0.3238 - F1: 0.3120
sub_1:Test (Best Model) - Loss: 1.7557 - Accuracy: 0.3810 - F1: 0.3913
sub_7:Test (Best Model) - Loss: 2.5372 - Accuracy: 0.3381 - F1: 0.3244
sub_14:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.4143 - F1: 0.3796
sub_5:Test (Best Model) - Loss: 1.5899 - Accuracy: 0.3762 - F1: 0.3805
sub_6:Test (Best Model) - Loss: 2.1104 - Accuracy: 0.3571 - F1: 0.3554
sub_4:Test (Best Model) - Loss: 2.2083 - Accuracy: 0.3810 - F1: 0.3887
sub_2:Test (Best Model) - Loss: 1.6612 - Accuracy: 0.4762 - F1: 0.4718
sub_13:Test (Best Model) - Loss: 2.3319 - Accuracy: 0.3714 - F1: 0.3532
sub_8:Test (Best Model) - Loss: 2.0680 - Accuracy: 0.4286 - F1: 0.3974
sub_14:Test (Best Model) - Loss: 1.6740 - Accuracy: 0.4333 - F1: 0.3987
sub_10:Test (Best Model) - Loss: 2.7142 - Accuracy: 0.2476 - F1: 0.2182
sub_1:Test (Best Model) - Loss: 1.7915 - Accuracy: 0.4143 - F1: 0.4182
sub_11:Test (Best Model) - Loss: 2.1945 - Accuracy: 0.3857 - F1: 0.3794
sub_6:Test (Best Model) - Loss: 1.9549 - Accuracy: 0.3571 - F1: 0.3572
sub_12:Test (Best Model) - Loss: 2.5490 - Accuracy: 0.3238 - F1: 0.3181
sub_3:Test (Best Model) - Loss: 2.0776 - Accuracy: 0.3095 - F1: 0.3079
sub_7:Test (Best Model) - Loss: 1.9631 - Accuracy: 0.3571 - F1: 0.3347
sub_9:Test (Best Model) - Loss: 2.3559 - Accuracy: 0.3429 - F1: 0.3409
sub_4:Test (Best Model) - Loss: 2.1723 - Accuracy: 0.3524 - F1: 0.3530
sub_8:Test (Best Model) - Loss: 1.6554 - Accuracy: 0.4286 - F1: 0.3929
sub_13:Test (Best Model) - Loss: 1.6892 - Accuracy: 0.3762 - F1: 0.3584
sub_5:Test (Best Model) - Loss: 2.1026 - Accuracy: 0.4333 - F1: 0.4109
sub_10:Test (Best Model) - Loss: 1.9070 - Accuracy: 0.3286 - F1: 0.3137
sub_11:Test (Best Model) - Loss: 1.8676 - Accuracy: 0.4095 - F1: 0.3980
sub_12:Test (Best Model) - Loss: 2.0178 - Accuracy: 0.3190 - F1: 0.3246
sub_9:Test (Best Model) - Loss: 1.5280 - Accuracy: 0.3952 - F1: 0.3996
sub_13:Test (Best Model) - Loss: 1.7104 - Accuracy: 0.4000 - F1: 0.3591
sub_4:Test (Best Model) - Loss: 2.0983 - Accuracy: 0.3571 - F1: 0.3682
sub_10:Test (Best Model) - Loss: 2.2027 - Accuracy: 0.3381 - F1: 0.3282
sub_2:Test (Best Model) - Loss: 1.7964 - Accuracy: 0.4762 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 1.8455 - Accuracy: 0.4381 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 2.1513 - Accuracy: 0.3619 - F1: 0.3290
sub_8:Test (Best Model) - Loss: 1.9462 - Accuracy: 0.4000 - F1: 0.3651
sub_1:Test (Best Model) - Loss: 2.4587 - Accuracy: 0.3476 - F1: 0.3588
sub_6:Test (Best Model) - Loss: 2.2277 - Accuracy: 0.3810 - F1: 0.3874
sub_3:Test (Best Model) - Loss: 2.4070 - Accuracy: 0.3667 - F1: 0.3442
sub_11:Test (Best Model) - Loss: 1.6732 - Accuracy: 0.4571 - F1: 0.4434
sub_2:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.4810 - F1: 0.4741
sub_10:Test (Best Model) - Loss: 1.9146 - Accuracy: 0.3143 - F1: 0.3148
sub_7:Test (Best Model) - Loss: 1.8295 - Accuracy: 0.3381 - F1: 0.3204
sub_6:Test (Best Model) - Loss: 1.7184 - Accuracy: 0.3762 - F1: 0.3782
sub_13:Test (Best Model) - Loss: 2.0308 - Accuracy: 0.3810 - F1: 0.3552
sub_4:Test (Best Model) - Loss: 2.1965 - Accuracy: 0.3381 - F1: 0.3398
sub_5:Test (Best Model) - Loss: 1.8424 - Accuracy: 0.4429 - F1: 0.4255
sub_3:Test (Best Model) - Loss: 1.8762 - Accuracy: 0.3095 - F1: 0.3155
sub_12:Test (Best Model) - Loss: 2.5889 - Accuracy: 0.3000 - F1: 0.2832
sub_11:Test (Best Model) - Loss: 2.0136 - Accuracy: 0.4000 - F1: 0.4019
sub_2:Test (Best Model) - Loss: 1.5107 - Accuracy: 0.4619 - F1: 0.4476
sub_10:Test (Best Model) - Loss: 1.8274 - Accuracy: 0.2857 - F1: 0.2556
sub_9:Test (Best Model) - Loss: 2.5787 - Accuracy: 0.3429 - F1: 0.3358
sub_1:Test (Best Model) - Loss: 2.7434 - Accuracy: 0.3190 - F1: 0.3274
sub_5:Test (Best Model) - Loss: 1.5472 - Accuracy: 0.4524 - F1: 0.4307
sub_7:Test (Best Model) - Loss: 2.2691 - Accuracy: 0.3429 - F1: 0.3252
sub_3:Test (Best Model) - Loss: 2.0092 - Accuracy: 0.3190 - F1: 0.3209
sub_13:Test (Best Model) - Loss: 2.1435 - Accuracy: 0.3810 - F1: 0.3699
sub_11:Test (Best Model) - Loss: 2.2010 - Accuracy: 0.4143 - F1: 0.4121
sub_1:Test (Best Model) - Loss: 1.8984 - Accuracy: 0.3667 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 1.8920 - Accuracy: 0.4048 - F1: 0.3705
sub_3:Test (Best Model) - Loss: 1.8957 - Accuracy: 0.3524 - F1: 0.3409
sub_1:Test (Best Model) - Loss: 1.7214 - Accuracy: 0.3905 - F1: 0.3957
sub_11:Test (Best Model) - Loss: 1.9076 - Accuracy: 0.4143 - F1: 0.4063
sub_1:Test (Best Model) - Loss: 2.2162 - Accuracy: 0.3762 - F1: 0.3605

=== Summary Results ===

acc: 38.78 ± 3.53
F1: 37.41 ± 3.65
acc-in: 46.93 ± 3.18
F1-in: 45.28 ± 3.23
