lr: 1e-05
sub_4:Test (Best Model) - Loss: 1.5523 - Accuracy: 0.3619 - F1: 0.3045
sub_3:Test (Best Model) - Loss: 1.5857 - Accuracy: 0.3238 - F1: 0.3104
sub_8:Test (Best Model) - Loss: 1.4936 - Accuracy: 0.4000 - F1: 0.3584
sub_2:Test (Best Model) - Loss: 1.5446 - Accuracy: 0.3095 - F1: 0.2365
sub_10:Test (Best Model) - Loss: 1.5387 - Accuracy: 0.3762 - F1: 0.3069
sub_12:Test (Best Model) - Loss: 1.5392 - Accuracy: 0.4238 - F1: 0.3941
sub_14:Test (Best Model) - Loss: 1.5276 - Accuracy: 0.3571 - F1: 0.3136
sub_6:Test (Best Model) - Loss: 1.5356 - Accuracy: 0.3857 - F1: 0.2893
sub_11:Test (Best Model) - Loss: 1.5163 - Accuracy: 0.4000 - F1: 0.3593
sub_4:Test (Best Model) - Loss: 1.5314 - Accuracy: 0.3524 - F1: 0.3363
sub_1:Test (Best Model) - Loss: 1.5601 - Accuracy: 0.3333 - F1: 0.2905
sub_13:Test (Best Model) - Loss: 1.5534 - Accuracy: 0.3429 - F1: 0.2665
sub_5:Test (Best Model) - Loss: 1.5759 - Accuracy: 0.3048 - F1: 0.2912
sub_9:Test (Best Model) - Loss: 1.4929 - Accuracy: 0.4476 - F1: 0.3798
sub_7:Test (Best Model) - Loss: 1.5778 - Accuracy: 0.3048 - F1: 0.2672
sub_12:Test (Best Model) - Loss: 1.5640 - Accuracy: 0.2714 - F1: 0.2843
sub_8:Test (Best Model) - Loss: 1.4587 - Accuracy: 0.4810 - F1: 0.4867
sub_2:Test (Best Model) - Loss: 1.4983 - Accuracy: 0.4190 - F1: 0.3444
sub_4:Test (Best Model) - Loss: 1.5717 - Accuracy: 0.2810 - F1: 0.2701
sub_14:Test (Best Model) - Loss: 1.5292 - Accuracy: 0.4000 - F1: 0.3604
sub_6:Test (Best Model) - Loss: 1.5668 - Accuracy: 0.3476 - F1: 0.2701
sub_13:Test (Best Model) - Loss: 1.5860 - Accuracy: 0.2667 - F1: 0.2561
sub_10:Test (Best Model) - Loss: 1.5439 - Accuracy: 0.3857 - F1: 0.3359
sub_3:Test (Best Model) - Loss: 1.5813 - Accuracy: 0.2905 - F1: 0.1983
sub_12:Test (Best Model) - Loss: 1.5580 - Accuracy: 0.2952 - F1: 0.2852
sub_8:Test (Best Model) - Loss: 1.5269 - Accuracy: 0.4571 - F1: 0.4301
sub_4:Test (Best Model) - Loss: 1.5596 - Accuracy: 0.3810 - F1: 0.3475
sub_6:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.3190 - F1: 0.2612
sub_2:Test (Best Model) - Loss: 1.5457 - Accuracy: 0.3143 - F1: 0.2547
sub_14:Test (Best Model) - Loss: 1.5296 - Accuracy: 0.4143 - F1: 0.3823
sub_1:Test (Best Model) - Loss: 1.5565 - Accuracy: 0.3286 - F1: 0.2566
sub_11:Test (Best Model) - Loss: 1.5032 - Accuracy: 0.3905 - F1: 0.3378
sub_10:Test (Best Model) - Loss: 1.5577 - Accuracy: 0.3333 - F1: 0.2332
sub_12:Test (Best Model) - Loss: 1.5525 - Accuracy: 0.3476 - F1: 0.3024
sub_9:Test (Best Model) - Loss: 1.5148 - Accuracy: 0.4143 - F1: 0.3222
sub_8:Test (Best Model) - Loss: 1.4929 - Accuracy: 0.4571 - F1: 0.4358
sub_13:Test (Best Model) - Loss: 1.5592 - Accuracy: 0.3286 - F1: 0.2750
sub_4:Test (Best Model) - Loss: 1.5321 - Accuracy: 0.3524 - F1: 0.3059
sub_7:Test (Best Model) - Loss: 1.5953 - Accuracy: 0.2238 - F1: 0.2093
sub_3:Test (Best Model) - Loss: 1.5734 - Accuracy: 0.3619 - F1: 0.3234
sub_6:Test (Best Model) - Loss: 1.5480 - Accuracy: 0.3619 - F1: 0.3134
sub_10:Test (Best Model) - Loss: 1.5602 - Accuracy: 0.2762 - F1: 0.1996
sub_2:Test (Best Model) - Loss: 1.5327 - Accuracy: 0.3000 - F1: 0.2173
sub_14:Test (Best Model) - Loss: 1.5297 - Accuracy: 0.4190 - F1: 0.4130
sub_8:Test (Best Model) - Loss: 1.5410 - Accuracy: 0.3952 - F1: 0.3285
sub_5:Test (Best Model) - Loss: 1.5384 - Accuracy: 0.3381 - F1: 0.2404
sub_13:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.3190 - F1: 0.2464
sub_12:Test (Best Model) - Loss: 1.5049 - Accuracy: 0.4238 - F1: 0.4257
sub_11:Test (Best Model) - Loss: 1.5472 - Accuracy: 0.3714 - F1: 0.3378
sub_3:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.3095 - F1: 0.2396
sub_9:Test (Best Model) - Loss: 1.5430 - Accuracy: 0.4095 - F1: 0.2970
sub_1:Test (Best Model) - Loss: 1.5636 - Accuracy: 0.3333 - F1: 0.2459
sub_2:Test (Best Model) - Loss: 1.5490 - Accuracy: 0.2952 - F1: 0.2196
sub_6:Test (Best Model) - Loss: 1.5701 - Accuracy: 0.3095 - F1: 0.2513
sub_7:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.2619 - F1: 0.2202
sub_10:Test (Best Model) - Loss: 1.5514 - Accuracy: 0.3000 - F1: 0.2115
sub_14:Test (Best Model) - Loss: 1.5132 - Accuracy: 0.4095 - F1: 0.3514
sub_4:Test (Best Model) - Loss: 1.5049 - Accuracy: 0.4000 - F1: 0.3615
sub_5:Test (Best Model) - Loss: 1.5805 - Accuracy: 0.2952 - F1: 0.2272
sub_9:Test (Best Model) - Loss: 1.5629 - Accuracy: 0.3238 - F1: 0.2556
sub_8:Test (Best Model) - Loss: 1.4665 - Accuracy: 0.4905 - F1: 0.4838
sub_13:Test (Best Model) - Loss: 1.5622 - Accuracy: 0.3476 - F1: 0.2436
sub_3:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.2429 - F1: 0.1411
sub_12:Test (Best Model) - Loss: 1.5613 - Accuracy: 0.3286 - F1: 0.2855
sub_6:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.3476 - F1: 0.3143
sub_11:Test (Best Model) - Loss: 1.5284 - Accuracy: 0.4048 - F1: 0.3496
sub_1:Test (Best Model) - Loss: 1.5607 - Accuracy: 0.2762 - F1: 0.1924
sub_10:Test (Best Model) - Loss: 1.5382 - Accuracy: 0.4190 - F1: 0.4013
sub_5:Test (Best Model) - Loss: 1.5943 - Accuracy: 0.2429 - F1: 0.1851
sub_14:Test (Best Model) - Loss: 1.5415 - Accuracy: 0.3857 - F1: 0.3392
sub_2:Test (Best Model) - Loss: 1.5194 - Accuracy: 0.4048 - F1: 0.3933
sub_4:Test (Best Model) - Loss: 1.5246 - Accuracy: 0.4000 - F1: 0.4001
sub_12:Test (Best Model) - Loss: 1.5809 - Accuracy: 0.2762 - F1: 0.2410
sub_8:Test (Best Model) - Loss: 1.5098 - Accuracy: 0.4238 - F1: 0.3984
sub_7:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.2857 - F1: 0.2290
sub_9:Test (Best Model) - Loss: 1.4961 - Accuracy: 0.4619 - F1: 0.4186
sub_13:Test (Best Model) - Loss: 1.5540 - Accuracy: 0.3619 - F1: 0.3527
sub_3:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.3619 - F1: 0.3251
sub_4:Test (Best Model) - Loss: 1.5390 - Accuracy: 0.4048 - F1: 0.3772
sub_8:Test (Best Model) - Loss: 1.5102 - Accuracy: 0.4000 - F1: 0.3658
sub_11:Test (Best Model) - Loss: 1.5240 - Accuracy: 0.4048 - F1: 0.3361
sub_7:Test (Best Model) - Loss: 1.5876 - Accuracy: 0.3000 - F1: 0.2229
sub_1:Test (Best Model) - Loss: 1.5314 - Accuracy: 0.3048 - F1: 0.2207
sub_6:Test (Best Model) - Loss: 1.5677 - Accuracy: 0.3190 - F1: 0.2818
sub_12:Test (Best Model) - Loss: 1.5513 - Accuracy: 0.3190 - F1: 0.2441
sub_3:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.2857 - F1: 0.2540
sub_10:Test (Best Model) - Loss: 1.4872 - Accuracy: 0.4476 - F1: 0.4269
sub_2:Test (Best Model) - Loss: 1.5307 - Accuracy: 0.3667 - F1: 0.3654
sub_9:Test (Best Model) - Loss: 1.5339 - Accuracy: 0.3905 - F1: 0.3376
sub_7:Test (Best Model) - Loss: 1.5945 - Accuracy: 0.2619 - F1: 0.2398
sub_14:Test (Best Model) - Loss: 1.4821 - Accuracy: 0.4762 - F1: 0.4312
sub_8:Test (Best Model) - Loss: 1.5232 - Accuracy: 0.3857 - F1: 0.3414
sub_13:Test (Best Model) - Loss: 1.5535 - Accuracy: 0.3143 - F1: 0.2791
sub_3:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.1905 - F1: 0.1908
sub_4:Test (Best Model) - Loss: 1.5150 - Accuracy: 0.4000 - F1: 0.3609
sub_6:Test (Best Model) - Loss: 1.5722 - Accuracy: 0.3476 - F1: 0.3374
sub_11:Test (Best Model) - Loss: 1.5277 - Accuracy: 0.4238 - F1: 0.3901
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2333 - F1: 0.2340
sub_1:Test (Best Model) - Loss: 1.5662 - Accuracy: 0.3476 - F1: 0.3617
sub_5:Test (Best Model) - Loss: 1.5502 - Accuracy: 0.3143 - F1: 0.2267
sub_2:Test (Best Model) - Loss: 1.5058 - Accuracy: 0.4238 - F1: 0.4053
sub_12:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.2667 - F1: 0.2069
sub_8:Test (Best Model) - Loss: 1.4665 - Accuracy: 0.4619 - F1: 0.4246
sub_14:Test (Best Model) - Loss: 1.5333 - Accuracy: 0.4333 - F1: 0.4375
sub_10:Test (Best Model) - Loss: 1.5227 - Accuracy: 0.4286 - F1: 0.3954
sub_13:Test (Best Model) - Loss: 1.5733 - Accuracy: 0.3048 - F1: 0.2774
sub_4:Test (Best Model) - Loss: 1.5059 - Accuracy: 0.4143 - F1: 0.3682
sub_9:Test (Best Model) - Loss: 1.5390 - Accuracy: 0.4333 - F1: 0.4167
sub_11:Test (Best Model) - Loss: 1.5051 - Accuracy: 0.4381 - F1: 0.4076
sub_7:Test (Best Model) - Loss: 1.5797 - Accuracy: 0.3143 - F1: 0.3068
sub_3:Test (Best Model) - Loss: 1.5393 - Accuracy: 0.3619 - F1: 0.3518
sub_12:Test (Best Model) - Loss: 1.5531 - Accuracy: 0.2857 - F1: 0.2073
sub_8:Test (Best Model) - Loss: 1.5230 - Accuracy: 0.4143 - F1: 0.3773
sub_1:Test (Best Model) - Loss: 1.5434 - Accuracy: 0.3095 - F1: 0.2957
sub_2:Test (Best Model) - Loss: 1.5071 - Accuracy: 0.3667 - F1: 0.2907
sub_5:Test (Best Model) - Loss: 1.5687 - Accuracy: 0.3000 - F1: 0.2872
sub_6:Test (Best Model) - Loss: 1.5565 - Accuracy: 0.3381 - F1: 0.3317
sub_14:Test (Best Model) - Loss: 1.5181 - Accuracy: 0.4000 - F1: 0.3415
sub_4:Test (Best Model) - Loss: 1.5625 - Accuracy: 0.3619 - F1: 0.3285
sub_7:Test (Best Model) - Loss: 1.6145 - Accuracy: 0.2238 - F1: 0.1900
sub_10:Test (Best Model) - Loss: 1.5131 - Accuracy: 0.3905 - F1: 0.3483
sub_11:Test (Best Model) - Loss: 1.5010 - Accuracy: 0.4333 - F1: 0.4000
sub_13:Test (Best Model) - Loss: 1.5153 - Accuracy: 0.4000 - F1: 0.3751
sub_9:Test (Best Model) - Loss: 1.5304 - Accuracy: 0.3524 - F1: 0.2779
sub_1:Test (Best Model) - Loss: 1.5379 - Accuracy: 0.3571 - F1: 0.3197
sub_8:Test (Best Model) - Loss: 1.5308 - Accuracy: 0.4000 - F1: 0.3756
sub_6:Test (Best Model) - Loss: 1.5570 - Accuracy: 0.3286 - F1: 0.2959
sub_3:Test (Best Model) - Loss: 1.5148 - Accuracy: 0.3952 - F1: 0.3857
sub_14:Test (Best Model) - Loss: 1.4709 - Accuracy: 0.4714 - F1: 0.4171
sub_10:Test (Best Model) - Loss: 1.5107 - Accuracy: 0.4000 - F1: 0.3602
sub_7:Test (Best Model) - Loss: 1.5652 - Accuracy: 0.3619 - F1: 0.3089
sub_12:Test (Best Model) - Loss: 1.5583 - Accuracy: 0.3905 - F1: 0.2964
sub_4:Test (Best Model) - Loss: 1.5401 - Accuracy: 0.4143 - F1: 0.4042
sub_5:Test (Best Model) - Loss: 1.5178 - Accuracy: 0.3286 - F1: 0.3135
sub_2:Test (Best Model) - Loss: 1.4864 - Accuracy: 0.3810 - F1: 0.3253
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1857 - F1: 0.1840
sub_13:Test (Best Model) - Loss: 1.5140 - Accuracy: 0.4143 - F1: 0.3562
sub_8:Test (Best Model) - Loss: 1.5036 - Accuracy: 0.4190 - F1: 0.3741
sub_6:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.2952 - F1: 0.2377
sub_3:Test (Best Model) - Loss: 1.5859 - Accuracy: 0.2905 - F1: 0.2552
sub_10:Test (Best Model) - Loss: 1.5808 - Accuracy: 0.2857 - F1: 0.2585
sub_14:Test (Best Model) - Loss: 1.5850 - Accuracy: 0.2762 - F1: 0.2070
sub_2:Test (Best Model) - Loss: 1.5410 - Accuracy: 0.3429 - F1: 0.3390
sub_8:Test (Best Model) - Loss: 1.5226 - Accuracy: 0.4048 - F1: 0.3527
sub_7:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2524 - F1: 0.2318
sub_6:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2524 - F1: 0.2160
sub_1:Test (Best Model) - Loss: 1.4843 - Accuracy: 0.4143 - F1: 0.4129
sub_11:Test (Best Model) - Loss: 1.4604 - Accuracy: 0.4048 - F1: 0.3730
sub_4:Test (Best Model) - Loss: 1.5161 - Accuracy: 0.4667 - F1: 0.4151
sub_9:Test (Best Model) - Loss: 1.5201 - Accuracy: 0.3619 - F1: 0.2757
sub_10:Test (Best Model) - Loss: 1.5909 - Accuracy: 0.2571 - F1: 0.2304
sub_5:Test (Best Model) - Loss: 1.5146 - Accuracy: 0.4333 - F1: 0.4231
sub_12:Test (Best Model) - Loss: 1.5152 - Accuracy: 0.3810 - F1: 0.3036
sub_7:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.2095 - F1: 0.1789
sub_6:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2905 - F1: 0.2619
sub_3:Test (Best Model) - Loss: 1.5722 - Accuracy: 0.3095 - F1: 0.2926
sub_2:Test (Best Model) - Loss: 1.5404 - Accuracy: 0.3524 - F1: 0.3505
sub_8:Test (Best Model) - Loss: 1.5391 - Accuracy: 0.3952 - F1: 0.3683
sub_13:Test (Best Model) - Loss: 1.5582 - Accuracy: 0.4190 - F1: 0.3203
sub_2:Test (Best Model) - Loss: 1.5702 - Accuracy: 0.3190 - F1: 0.2863
sub_14:Test (Best Model) - Loss: 1.5808 - Accuracy: 0.2857 - F1: 0.2131
sub_1:Test (Best Model) - Loss: 1.5382 - Accuracy: 0.3381 - F1: 0.3140
sub_11:Test (Best Model) - Loss: 1.5118 - Accuracy: 0.4429 - F1: 0.3830
sub_6:Test (Best Model) - Loss: 1.5939 - Accuracy: 0.2810 - F1: 0.2131
sub_4:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.4048 - F1: 0.3515
sub_7:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2143 - F1: 0.1860
sub_5:Test (Best Model) - Loss: 1.5347 - Accuracy: 0.3810 - F1: 0.3276
sub_12:Test (Best Model) - Loss: 1.5590 - Accuracy: 0.3619 - F1: 0.3001
sub_9:Test (Best Model) - Loss: 1.4927 - Accuracy: 0.3667 - F1: 0.2908
sub_10:Test (Best Model) - Loss: 1.5666 - Accuracy: 0.3143 - F1: 0.2909
sub_6:Test (Best Model) - Loss: 1.5957 - Accuracy: 0.2810 - F1: 0.2463
sub_2:Test (Best Model) - Loss: 1.5436 - Accuracy: 0.4095 - F1: 0.3545
sub_13:Test (Best Model) - Loss: 1.5381 - Accuracy: 0.4095 - F1: 0.3151
sub_14:Test (Best Model) - Loss: 1.5736 - Accuracy: 0.2381 - F1: 0.1455
sub_3:Test (Best Model) - Loss: 1.5812 - Accuracy: 0.2905 - F1: 0.2438
sub_1:Test (Best Model) - Loss: 1.5419 - Accuracy: 0.3714 - F1: 0.3768
sub_12:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.3286 - F1: 0.2687
sub_7:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.2714 - F1: 0.2393
sub_11:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.4429 - F1: 0.4495
sub_5:Test (Best Model) - Loss: 1.5457 - Accuracy: 0.3905 - F1: 0.3128
sub_9:Test (Best Model) - Loss: 1.5703 - Accuracy: 0.2524 - F1: 0.2583
sub_4:Test (Best Model) - Loss: 1.5232 - Accuracy: 0.4429 - F1: 0.3991
sub_2:Test (Best Model) - Loss: 1.5305 - Accuracy: 0.4333 - F1: 0.4084
sub_10:Test (Best Model) - Loss: 1.5738 - Accuracy: 0.2619 - F1: 0.1795
sub_12:Test (Best Model) - Loss: 1.5667 - Accuracy: 0.2952 - F1: 0.2725
sub_9:Test (Best Model) - Loss: 1.5647 - Accuracy: 0.3476 - F1: 0.3196
sub_14:Test (Best Model) - Loss: 1.5806 - Accuracy: 0.2333 - F1: 0.1364
sub_3:Test (Best Model) - Loss: 1.5786 - Accuracy: 0.2857 - F1: 0.2753
sub_1:Test (Best Model) - Loss: 1.5204 - Accuracy: 0.4286 - F1: 0.4128
sub_13:Test (Best Model) - Loss: 1.4965 - Accuracy: 0.4571 - F1: 0.4138
sub_10:Test (Best Model) - Loss: 1.5795 - Accuracy: 0.3190 - F1: 0.2713
sub_3:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.2714 - F1: 0.2375
sub_14:Test (Best Model) - Loss: 1.5850 - Accuracy: 0.2429 - F1: 0.1563
sub_9:Test (Best Model) - Loss: 1.5454 - Accuracy: 0.3667 - F1: 0.3439
sub_11:Test (Best Model) - Loss: 1.4893 - Accuracy: 0.5333 - F1: 0.5212
sub_1:Test (Best Model) - Loss: 1.5525 - Accuracy: 0.3381 - F1: 0.2998
sub_5:Test (Best Model) - Loss: 1.5432 - Accuracy: 0.2286 - F1: 0.2331
sub_13:Test (Best Model) - Loss: 1.5187 - Accuracy: 0.4238 - F1: 0.3296
sub_9:Test (Best Model) - Loss: 1.5490 - Accuracy: 0.3476 - F1: 0.3351
sub_13:Test (Best Model) - Loss: 1.5602 - Accuracy: 0.4190 - F1: 0.3623
sub_11:Test (Best Model) - Loss: 1.5262 - Accuracy: 0.3762 - F1: 0.3647
sub_5:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.2810 - F1: 0.2671
sub_1:Test (Best Model) - Loss: 1.5135 - Accuracy: 0.3857 - F1: 0.3560
sub_9:Test (Best Model) - Loss: 1.5360 - Accuracy: 0.3714 - F1: 0.3598
sub_11:Test (Best Model) - Loss: 1.5184 - Accuracy: 0.4333 - F1: 0.3925
sub_5:Test (Best Model) - Loss: 1.5401 - Accuracy: 0.3095 - F1: 0.3248
sub_1:Test (Best Model) - Loss: 1.5171 - Accuracy: 0.3667 - F1: 0.3548
sub_11:Test (Best Model) - Loss: 1.5126 - Accuracy: 0.5143 - F1: 0.4342
sub_5:Test (Best Model) - Loss: 1.5409 - Accuracy: 0.3524 - F1: 0.3274
sub_5:Test (Best Model) - Loss: 1.5704 - Accuracy: 0.3333 - F1: 0.2842

=== Summary Results ===

acc: 35.35 ± 4.35
F1: 31.15 ± 4.34
acc-in: 40.23 ± 5.07
F1-in: 37.59 ± 5.12
