lr: 0.001
sub_8:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.3619 - F1: 0.2151
sub_12:Test (Best Model) - Loss: 1.5979 - Accuracy: 0.3190 - F1: 0.2236
sub_7:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.3667 - F1: 0.2482
sub_9:Test (Best Model) - Loss: 1.1451 - Accuracy: 0.4000 - F1: 0.2800
sub_3:Test (Best Model) - Loss: 5.1745 - Accuracy: 0.2524 - F1: 0.1514
sub_14:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.4190 - F1: 0.3908
sub_6:Test (Best Model) - Loss: 2.5452 - Accuracy: 0.2762 - F1: 0.1790
sub_11:Test (Best Model) - Loss: 1.4482 - Accuracy: 0.3810 - F1: 0.3163
sub_5:Test (Best Model) - Loss: 3.3719 - Accuracy: 0.3429 - F1: 0.2325
sub_10:Test (Best Model) - Loss: 1.6640 - Accuracy: 0.3048 - F1: 0.1877
sub_2:Test (Best Model) - Loss: 2.2721 - Accuracy: 0.2857 - F1: 0.1850
sub_13:Test (Best Model) - Loss: 2.4579 - Accuracy: 0.3238 - F1: 0.1857
sub_1:Test (Best Model) - Loss: 3.7845 - Accuracy: 0.2857 - F1: 0.1728
sub_8:Test (Best Model) - Loss: 1.8060 - Accuracy: 0.3857 - F1: 0.2460
sub_12:Test (Best Model) - Loss: 1.5518 - Accuracy: 0.2476 - F1: 0.1564
sub_7:Test (Best Model) - Loss: 1.6320 - Accuracy: 0.2619 - F1: 0.1660
sub_9:Test (Best Model) - Loss: 1.8566 - Accuracy: 0.3381 - F1: 0.1922
sub_11:Test (Best Model) - Loss: 1.4251 - Accuracy: 0.3952 - F1: 0.3221
sub_6:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.3619 - F1: 0.2878
sub_14:Test (Best Model) - Loss: 1.4310 - Accuracy: 0.3190 - F1: 0.2576
sub_10:Test (Best Model) - Loss: 1.8285 - Accuracy: 0.4000 - F1: 0.2695
sub_3:Test (Best Model) - Loss: 2.5588 - Accuracy: 0.3667 - F1: 0.2489
sub_5:Test (Best Model) - Loss: 2.3972 - Accuracy: 0.2714 - F1: 0.1821
sub_1:Test (Best Model) - Loss: 1.9358 - Accuracy: 0.3381 - F1: 0.2317
sub_8:Test (Best Model) - Loss: 1.4718 - Accuracy: 0.3810 - F1: 0.2598
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2571 - F1: 0.1592
sub_4:Test (Best Model) - Loss: 1.7773 - Accuracy: 0.4286 - F1: 0.3576
sub_11:Test (Best Model) - Loss: 1.4384 - Accuracy: 0.4810 - F1: 0.3959
sub_10:Test (Best Model) - Loss: 1.8091 - Accuracy: 0.3571 - F1: 0.2303
sub_6:Test (Best Model) - Loss: 1.6237 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.2896 - Accuracy: 0.4048 - F1: 0.2791
sub_2:Test (Best Model) - Loss: 4.4725 - Accuracy: 0.3524 - F1: 0.2448
sub_3:Test (Best Model) - Loss: 5.6333 - Accuracy: 0.3048 - F1: 0.1739
sub_13:Test (Best Model) - Loss: 1.5227 - Accuracy: 0.4667 - F1: 0.3718
sub_1:Test (Best Model) - Loss: 3.2007 - Accuracy: 0.2905 - F1: 0.1613
sub_8:Test (Best Model) - Loss: 1.4520 - Accuracy: 0.3857 - F1: 0.2545
sub_5:Test (Best Model) - Loss: 3.0963 - Accuracy: 0.3714 - F1: 0.2743
sub_7:Test (Best Model) - Loss: 1.5578 - Accuracy: 0.2952 - F1: 0.1783
sub_4:Test (Best Model) - Loss: 1.7714 - Accuracy: 0.3476 - F1: 0.2259
sub_9:Test (Best Model) - Loss: 2.0221 - Accuracy: 0.3524 - F1: 0.2308
sub_12:Test (Best Model) - Loss: 1.2693 - Accuracy: 0.3810 - F1: 0.2707
sub_10:Test (Best Model) - Loss: 1.4278 - Accuracy: 0.4000 - F1: 0.2624
sub_13:Test (Best Model) - Loss: 2.9931 - Accuracy: 0.2095 - F1: 0.0905
sub_1:Test (Best Model) - Loss: 2.3945 - Accuracy: 0.3286 - F1: 0.1901
sub_8:Test (Best Model) - Loss: 1.6261 - Accuracy: 0.3810 - F1: 0.2404
sub_14:Test (Best Model) - Loss: 1.5824 - Accuracy: 0.5048 - F1: 0.4261
sub_3:Test (Best Model) - Loss: 5.2001 - Accuracy: 0.2762 - F1: 0.1501
sub_6:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3524 - F1: 0.2248
sub_7:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.3143 - F1: 0.2173
sub_5:Test (Best Model) - Loss: 2.3737 - Accuracy: 0.1952 - F1: 0.0799
sub_12:Test (Best Model) - Loss: 1.6933 - Accuracy: 0.2714 - F1: 0.1761
sub_10:Test (Best Model) - Loss: 1.4892 - Accuracy: 0.4429 - F1: 0.3283
sub_2:Test (Best Model) - Loss: 1.8884 - Accuracy: 0.3762 - F1: 0.2360
sub_1:Test (Best Model) - Loss: 3.6248 - Accuracy: 0.3000 - F1: 0.1733
sub_4:Test (Best Model) - Loss: 1.5542 - Accuracy: 0.4048 - F1: 0.3372
sub_8:Test (Best Model) - Loss: 1.1489 - Accuracy: 0.4000 - F1: 0.2784
sub_14:Test (Best Model) - Loss: 1.2014 - Accuracy: 0.5429 - F1: 0.4722
sub_6:Test (Best Model) - Loss: 1.2317 - Accuracy: 0.4000 - F1: 0.2690
sub_13:Test (Best Model) - Loss: 2.6128 - Accuracy: 0.3905 - F1: 0.2764
sub_3:Test (Best Model) - Loss: 4.0588 - Accuracy: 0.3048 - F1: 0.1699
sub_12:Test (Best Model) - Loss: 2.8469 - Accuracy: 0.3095 - F1: 0.1885
sub_10:Test (Best Model) - Loss: 1.4397 - Accuracy: 0.4190 - F1: 0.3147
sub_7:Test (Best Model) - Loss: 1.8782 - Accuracy: 0.3524 - F1: 0.2045
sub_11:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.5143 - F1: 0.4281
sub_4:Test (Best Model) - Loss: 1.9882 - Accuracy: 0.3381 - F1: 0.2469
sub_8:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.3810 - F1: 0.2595
sub_14:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.3619 - F1: 0.3710
sub_6:Test (Best Model) - Loss: 1.4476 - Accuracy: 0.3000 - F1: 0.2061
sub_13:Test (Best Model) - Loss: 3.9540 - Accuracy: 0.3048 - F1: 0.1900
sub_5:Test (Best Model) - Loss: 4.4688 - Accuracy: 0.3524 - F1: 0.2690
sub_3:Test (Best Model) - Loss: 1.1750 - Accuracy: 0.3857 - F1: 0.2715
sub_9:Test (Best Model) - Loss: 1.7766 - Accuracy: 0.4429 - F1: 0.3684
sub_12:Test (Best Model) - Loss: 6.1632 - Accuracy: 0.2762 - F1: 0.1513
sub_10:Test (Best Model) - Loss: 1.5112 - Accuracy: 0.3476 - F1: 0.2326
sub_11:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.4429 - F1: 0.3670
sub_6:Test (Best Model) - Loss: 1.2320 - Accuracy: 0.3714 - F1: 0.2624
sub_2:Test (Best Model) - Loss: 2.3577 - Accuracy: 0.3667 - F1: 0.2790
sub_13:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.3429 - F1: 0.2638
sub_3:Test (Best Model) - Loss: 1.5206 - Accuracy: 0.2524 - F1: 0.1559
sub_9:Test (Best Model) - Loss: 1.2169 - Accuracy: 0.4000 - F1: 0.2794
sub_4:Test (Best Model) - Loss: 1.9948 - Accuracy: 0.3952 - F1: 0.2639
sub_7:Test (Best Model) - Loss: 1.7700 - Accuracy: 0.3905 - F1: 0.2436
sub_14:Test (Best Model) - Loss: 1.2292 - Accuracy: 0.4857 - F1: 0.4148
sub_12:Test (Best Model) - Loss: 3.7517 - Accuracy: 0.3048 - F1: 0.1721
sub_1:Test (Best Model) - Loss: 1.5404 - Accuracy: 0.4190 - F1: 0.3869
sub_8:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.4000 - F1: 0.2800
sub_10:Test (Best Model) - Loss: 1.2852 - Accuracy: 0.3857 - F1: 0.2647
sub_5:Test (Best Model) - Loss: 1.4189 - Accuracy: 0.3905 - F1: 0.3608
sub_6:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3333 - F1: 0.2230
sub_2:Test (Best Model) - Loss: 1.8998 - Accuracy: 0.4095 - F1: 0.2869
sub_4:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.3905 - F1: 0.2820
sub_9:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.3810 - F1: 0.2490
sub_11:Test (Best Model) - Loss: 1.4110 - Accuracy: 0.4619 - F1: 0.3703
sub_14:Test (Best Model) - Loss: 1.1250 - Accuracy: 0.5333 - F1: 0.4464
sub_12:Test (Best Model) - Loss: 3.1306 - Accuracy: 0.3381 - F1: 0.1988
sub_7:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.4238 - F1: 0.3405
sub_3:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.3619 - F1: 0.2567
sub_8:Test (Best Model) - Loss: 1.2209 - Accuracy: 0.4000 - F1: 0.2800
sub_13:Test (Best Model) - Loss: 1.4049 - Accuracy: 0.3286 - F1: 0.2198
sub_6:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.4861 - Accuracy: 0.3857 - F1: 0.2978
sub_2:Test (Best Model) - Loss: 1.1982 - Accuracy: 0.5048 - F1: 0.4339
sub_4:Test (Best Model) - Loss: 1.6370 - Accuracy: 0.3905 - F1: 0.3181
sub_9:Test (Best Model) - Loss: 2.1941 - Accuracy: 0.3857 - F1: 0.2389
sub_11:Test (Best Model) - Loss: 1.5039 - Accuracy: 0.4095 - F1: 0.3794
sub_7:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.2439 - Accuracy: 0.3905 - F1: 0.2733
sub_13:Test (Best Model) - Loss: 1.5068 - Accuracy: 0.3810 - F1: 0.2455
sub_5:Test (Best Model) - Loss: 1.3110 - Accuracy: 0.4381 - F1: 0.3384
sub_1:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.4381 - F1: 0.3786
sub_14:Test (Best Model) - Loss: 1.1998 - Accuracy: 0.4714 - F1: 0.3916
sub_3:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.3810 - F1: 0.2665
sub_10:Test (Best Model) - Loss: 1.7184 - Accuracy: 0.3952 - F1: 0.3496
sub_9:Test (Best Model) - Loss: 1.7280 - Accuracy: 0.2429 - F1: 0.1224
sub_12:Test (Best Model) - Loss: 3.3872 - Accuracy: 0.2810 - F1: 0.1832
sub_11:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.4667 - F1: 0.3954
sub_6:Test (Best Model) - Loss: 1.3256 - Accuracy: 0.3476 - F1: 0.2462
sub_13:Test (Best Model) - Loss: 1.3030 - Accuracy: 0.3571 - F1: 0.2492
sub_8:Test (Best Model) - Loss: 1.5071 - Accuracy: 0.3762 - F1: 0.2588
sub_1:Test (Best Model) - Loss: 1.3405 - Accuracy: 0.3381 - F1: 0.2387
sub_14:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.3381 - F1: 0.2368
sub_9:Test (Best Model) - Loss: 4.4864 - Accuracy: 0.2857 - F1: 0.1687
sub_12:Test (Best Model) - Loss: 1.2650 - Accuracy: 0.3810 - F1: 0.2642
sub_10:Test (Best Model) - Loss: 1.6984 - Accuracy: 0.4143 - F1: 0.3539
sub_5:Test (Best Model) - Loss: 1.9932 - Accuracy: 0.4571 - F1: 0.3934
sub_4:Test (Best Model) - Loss: 1.1479 - Accuracy: 0.5429 - F1: 0.5144
sub_11:Test (Best Model) - Loss: 1.4939 - Accuracy: 0.3905 - F1: 0.3263
sub_6:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.3381 - F1: 0.2387
sub_13:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.3619 - F1: 0.2493
sub_8:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.4429 - F1: 0.3412
sub_1:Test (Best Model) - Loss: 1.2169 - Accuracy: 0.3762 - F1: 0.2658
sub_2:Test (Best Model) - Loss: 1.1758 - Accuracy: 0.4714 - F1: 0.4264
sub_3:Test (Best Model) - Loss: 1.2236 - Accuracy: 0.3714 - F1: 0.2601
sub_7:Test (Best Model) - Loss: 2.1673 - Accuracy: 0.3571 - F1: 0.2136
sub_10:Test (Best Model) - Loss: 1.2313 - Accuracy: 0.3714 - F1: 0.2635
sub_14:Test (Best Model) - Loss: 1.2944 - Accuracy: 0.3619 - F1: 0.2522
sub_4:Test (Best Model) - Loss: 1.3341 - Accuracy: 0.3810 - F1: 0.3092
sub_9:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.1762 - F1: 0.1013
sub_6:Test (Best Model) - Loss: 1.2447 - Accuracy: 0.3762 - F1: 0.3063
sub_12:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.3619 - F1: 0.2511
sub_8:Test (Best Model) - Loss: 1.1675 - Accuracy: 0.3905 - F1: 0.2744
sub_11:Test (Best Model) - Loss: 1.4167 - Accuracy: 0.3524 - F1: 0.2385
sub_13:Test (Best Model) - Loss: 1.2016 - Accuracy: 0.4000 - F1: 0.3079
sub_3:Test (Best Model) - Loss: 2.5283 - Accuracy: 0.3381 - F1: 0.2076
sub_1:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.4286 - F1: 0.4009
sub_7:Test (Best Model) - Loss: 1.4965 - Accuracy: 0.3190 - F1: 0.2298
sub_4:Test (Best Model) - Loss: 1.5507 - Accuracy: 0.3524 - F1: 0.2326
sub_9:Test (Best Model) - Loss: 1.2640 - Accuracy: 0.3619 - F1: 0.2560
sub_10:Test (Best Model) - Loss: 1.5218 - Accuracy: 0.3000 - F1: 0.2727
sub_5:Test (Best Model) - Loss: 1.7616 - Accuracy: 0.4952 - F1: 0.4626
sub_6:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.3905 - F1: 0.2956
sub_2:Test (Best Model) - Loss: 1.1810 - Accuracy: 0.4857 - F1: 0.4189
sub_12:Test (Best Model) - Loss: 1.3274 - Accuracy: 0.3571 - F1: 0.2520
sub_8:Test (Best Model) - Loss: 1.1248 - Accuracy: 0.4000 - F1: 0.2800
sub_14:Test (Best Model) - Loss: 4.8348 - Accuracy: 0.2619 - F1: 0.1587
sub_11:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.4143 - F1: 0.3207
sub_3:Test (Best Model) - Loss: 1.4780 - Accuracy: 0.3048 - F1: 0.2159
sub_4:Test (Best Model) - Loss: 1.5106 - Accuracy: 0.3190 - F1: 0.2218
sub_10:Test (Best Model) - Loss: 1.4209 - Accuracy: 0.3381 - F1: 0.2553
sub_1:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3333 - F1: 0.2364
sub_9:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.3190 - F1: 0.2236
sub_13:Test (Best Model) - Loss: 1.4794 - Accuracy: 0.3524 - F1: 0.2068
sub_12:Test (Best Model) - Loss: 1.3269 - Accuracy: 0.3714 - F1: 0.2477
sub_11:Test (Best Model) - Loss: 1.5591 - Accuracy: 0.3571 - F1: 0.3072
sub_3:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.2952 - F1: 0.2014
sub_8:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.3952 - F1: 0.2715
sub_7:Test (Best Model) - Loss: 1.4372 - Accuracy: 0.3810 - F1: 0.2566
sub_6:Test (Best Model) - Loss: 1.1844 - Accuracy: 0.3857 - F1: 0.2685
sub_1:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.3857 - F1: 0.2672
sub_2:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.3714 - F1: 0.2903
sub_10:Test (Best Model) - Loss: 1.6649 - Accuracy: 0.2619 - F1: 0.1651
sub_9:Test (Best Model) - Loss: 1.5392 - Accuracy: 0.3048 - F1: 0.2109
sub_13:Test (Best Model) - Loss: 1.5104 - Accuracy: 0.3667 - F1: 0.2702
sub_5:Test (Best Model) - Loss: 2.4563 - Accuracy: 0.4476 - F1: 0.3691
sub_14:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.3000 - F1: 0.2048
sub_4:Test (Best Model) - Loss: 1.2222 - Accuracy: 0.4143 - F1: 0.3548
sub_3:Test (Best Model) - Loss: 1.5040 - Accuracy: 0.2905 - F1: 0.1983
sub_6:Test (Best Model) - Loss: 1.7431 - Accuracy: 0.3286 - F1: 0.2200
sub_12:Test (Best Model) - Loss: 1.4730 - Accuracy: 0.3429 - F1: 0.2309
sub_7:Test (Best Model) - Loss: 1.4792 - Accuracy: 0.3571 - F1: 0.2454
sub_2:Test (Best Model) - Loss: 1.3081 - Accuracy: 0.3571 - F1: 0.2527
sub_9:Test (Best Model) - Loss: 1.5740 - Accuracy: 0.2286 - F1: 0.1183
sub_13:Test (Best Model) - Loss: 1.3346 - Accuracy: 0.3810 - F1: 0.2918
sub_1:Test (Best Model) - Loss: 1.4973 - Accuracy: 0.3571 - F1: 0.2506
sub_10:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.4095 - F1: 0.3310
sub_3:Test (Best Model) - Loss: 1.4946 - Accuracy: 0.3238 - F1: 0.2257
sub_5:Test (Best Model) - Loss: 1.2580 - Accuracy: 0.4476 - F1: 0.3934
sub_11:Test (Best Model) - Loss: 1.2036 - Accuracy: 0.4667 - F1: 0.4406
sub_7:Test (Best Model) - Loss: 1.4379 - Accuracy: 0.3476 - F1: 0.2255
sub_4:Test (Best Model) - Loss: 1.5122 - Accuracy: 0.5095 - F1: 0.4467
sub_9:Test (Best Model) - Loss: 1.5100 - Accuracy: 0.3095 - F1: 0.2149
sub_13:Test (Best Model) - Loss: 1.3965 - Accuracy: 0.3286 - F1: 0.2296
sub_1:Test (Best Model) - Loss: 1.2322 - Accuracy: 0.4905 - F1: 0.4558
sub_4:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.3429 - F1: 0.2865
sub_11:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.3905 - F1: 0.2768
sub_14:Test (Best Model) - Loss: 4.5486 - Accuracy: 0.3286 - F1: 0.2551
sub_5:Test (Best Model) - Loss: 1.5610 - Accuracy: 0.3381 - F1: 0.1972
sub_7:Test (Best Model) - Loss: 1.5313 - Accuracy: 0.3238 - F1: 0.2121
sub_2:Test (Best Model) - Loss: 1.8577 - Accuracy: 0.4333 - F1: 0.4009
sub_4:Test (Best Model) - Loss: 1.4260 - Accuracy: 0.3429 - F1: 0.2466
sub_14:Test (Best Model) - Loss: 5.0028 - Accuracy: 0.3095 - F1: 0.2243
sub_5:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.4333 - F1: 0.3611
sub_11:Test (Best Model) - Loss: 1.4862 - Accuracy: 0.4524 - F1: 0.4039
sub_14:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2857 - F1: 0.2079
sub_2:Test (Best Model) - Loss: 1.5101 - Accuracy: 0.3143 - F1: 0.2782
sub_5:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.3524 - F1: 0.2990
sub_5:Test (Best Model) - Loss: 1.5813 - Accuracy: 0.4429 - F1: 0.3913
sub_2:Test (Best Model) - Loss: 1.2929 - Accuracy: 0.4905 - F1: 0.4723
sub_2:Test (Best Model) - Loss: 1.6882 - Accuracy: 0.3762 - F1: 0.3371
sub_2:Test (Best Model) - Loss: 1.3064 - Accuracy: 0.4524 - F1: 0.4136

=== Summary Results ===

acc: 36.54 ± 3.23
F1: 26.80 ± 4.67
acc-in: 46.55 ± 4.93
F1-in: 37.59 ± 6.49
