lr: 0.001
sub_1:Test (Best Model) - Loss: 4.2266 - Accuracy: 0.3286 - F1: 0.2993
sub_3:Test (Best Model) - Loss: 7.4223 - Accuracy: 0.3333 - F1: 0.2674
sub_2:Test (Best Model) - Loss: 4.8260 - Accuracy: 0.3857 - F1: 0.3377
sub_1:Test (Best Model) - Loss: 5.0438 - Accuracy: 0.3190 - F1: 0.2669
sub_3:Test (Best Model) - Loss: 7.6732 - Accuracy: 0.2952 - F1: 0.2173
sub_2:Test (Best Model) - Loss: 4.3323 - Accuracy: 0.4143 - F1: 0.3517
sub_1:Test (Best Model) - Loss: 9.7397 - Accuracy: 0.3286 - F1: 0.2765
sub_3:Test (Best Model) - Loss: 10.3876 - Accuracy: 0.3048 - F1: 0.2173
sub_2:Test (Best Model) - Loss: 3.5569 - Accuracy: 0.4000 - F1: 0.3186
sub_1:Test (Best Model) - Loss: 4.6072 - Accuracy: 0.3286 - F1: 0.2878
sub_2:Test (Best Model) - Loss: 2.5941 - Accuracy: 0.4810 - F1: 0.4362
sub_3:Test (Best Model) - Loss: 5.5012 - Accuracy: 0.2762 - F1: 0.2015
sub_1:Test (Best Model) - Loss: 3.1831 - Accuracy: 0.3190 - F1: 0.2536
sub_3:Test (Best Model) - Loss: 8.7098 - Accuracy: 0.2905 - F1: 0.2135
sub_1:Test (Best Model) - Loss: 3.0189 - Accuracy: 0.3429 - F1: 0.2836
sub_2:Test (Best Model) - Loss: 9.0664 - Accuracy: 0.3381 - F1: 0.2739
sub_3:Test (Best Model) - Loss: 4.7046 - Accuracy: 0.3952 - F1: 0.3576
sub_1:Test (Best Model) - Loss: 4.2441 - Accuracy: 0.3429 - F1: 0.3027
sub_2:Test (Best Model) - Loss: 7.1032 - Accuracy: 0.3571 - F1: 0.3127
sub_1:Test (Best Model) - Loss: 2.2704 - Accuracy: 0.3714 - F1: 0.3365
sub_3:Test (Best Model) - Loss: 5.1701 - Accuracy: 0.3952 - F1: 0.3731
sub_1:Test (Best Model) - Loss: 4.6879 - Accuracy: 0.3524 - F1: 0.3030
sub_2:Test (Best Model) - Loss: 5.8095 - Accuracy: 0.3333 - F1: 0.3225
sub_3:Test (Best Model) - Loss: 3.2656 - Accuracy: 0.3714 - F1: 0.3531
sub_3:Test (Best Model) - Loss: 1.9083 - Accuracy: 0.3905 - F1: 0.3754
sub_1:Test (Best Model) - Loss: 2.0077 - Accuracy: 0.3762 - F1: 0.3385
sub_2:Test (Best Model) - Loss: 2.7535 - Accuracy: 0.4429 - F1: 0.4208
sub_3:Test (Best Model) - Loss: 3.7997 - Accuracy: 0.3905 - F1: 0.3675
sub_1:Test (Best Model) - Loss: 3.8194 - Accuracy: 0.4000 - F1: 0.3513
sub_2:Test (Best Model) - Loss: 3.6746 - Accuracy: 0.4476 - F1: 0.4515
sub_3:Test (Best Model) - Loss: 4.1213 - Accuracy: 0.3381 - F1: 0.3276
sub_2:Test (Best Model) - Loss: 1.8032 - Accuracy: 0.4190 - F1: 0.4266
sub_1:Test (Best Model) - Loss: 4.1508 - Accuracy: 0.3667 - F1: 0.3183
sub_3:Test (Best Model) - Loss: 5.4209 - Accuracy: 0.3143 - F1: 0.2998
sub_2:Test (Best Model) - Loss: 10.2783 - Accuracy: 0.2333 - F1: 0.1898
sub_3:Test (Best Model) - Loss: 2.4023 - Accuracy: 0.3429 - F1: 0.3403
sub_1:Test (Best Model) - Loss: 2.4759 - Accuracy: 0.4095 - F1: 0.3641
sub_2:Test (Best Model) - Loss: 8.1596 - Accuracy: 0.2524 - F1: 0.2292
sub_3:Test (Best Model) - Loss: 2.6306 - Accuracy: 0.3048 - F1: 0.2896
sub_1:Test (Best Model) - Loss: 2.9848 - Accuracy: 0.3571 - F1: 0.2972
sub_3:Test (Best Model) - Loss: 2.3488 - Accuracy: 0.3333 - F1: 0.3122
sub_1:Test (Best Model) - Loss: 2.7958 - Accuracy: 0.3667 - F1: 0.3063
sub_2:Test (Best Model) - Loss: 11.8238 - Accuracy: 0.2667 - F1: 0.2229
sub_2:Test (Best Model) - Loss: 5.7921 - Accuracy: 0.3143 - F1: 0.3034
sub_2:Test (Best Model) - Loss: 7.9310 - Accuracy: 0.3571 - F1: 0.3446
sub_4:Test (Best Model) - Loss: 3.0840 - Accuracy: 0.3333 - F1: 0.2992
sub_6:Test (Best Model) - Loss: 2.7215 - Accuracy: 0.3857 - F1: 0.3425
sub_4:Test (Best Model) - Loss: 2.3184 - Accuracy: 0.3476 - F1: 0.3059
sub_5:Test (Best Model) - Loss: 7.6994 - Accuracy: 0.3333 - F1: 0.2994
sub_4:Test (Best Model) - Loss: 2.9150 - Accuracy: 0.3524 - F1: 0.2912
sub_6:Test (Best Model) - Loss: 8.5206 - Accuracy: 0.3667 - F1: 0.2955
sub_5:Test (Best Model) - Loss: 15.7265 - Accuracy: 0.2762 - F1: 0.1981
sub_4:Test (Best Model) - Loss: 5.4545 - Accuracy: 0.3905 - F1: 0.3410
sub_6:Test (Best Model) - Loss: 4.4152 - Accuracy: 0.3619 - F1: 0.3388
sub_4:Test (Best Model) - Loss: 2.9648 - Accuracy: 0.3619 - F1: 0.3085
sub_5:Test (Best Model) - Loss: 8.9158 - Accuracy: 0.3143 - F1: 0.2897
sub_5:Test (Best Model) - Loss: 5.0491 - Accuracy: 0.3571 - F1: 0.3169
sub_4:Test (Best Model) - Loss: 12.8908 - Accuracy: 0.3333 - F1: 0.2921
sub_5:Test (Best Model) - Loss: 6.8963 - Accuracy: 0.3048 - F1: 0.2479
sub_6:Test (Best Model) - Loss: 8.8656 - Accuracy: 0.3429 - F1: 0.3240
sub_4:Test (Best Model) - Loss: 4.8287 - Accuracy: 0.4048 - F1: 0.3860
sub_6:Test (Best Model) - Loss: 5.3574 - Accuracy: 0.3619 - F1: 0.3662
sub_4:Test (Best Model) - Loss: 6.5744 - Accuracy: 0.3810 - F1: 0.3566
sub_5:Test (Best Model) - Loss: 5.2446 - Accuracy: 0.3048 - F1: 0.2468
sub_6:Test (Best Model) - Loss: 6.1466 - Accuracy: 0.3619 - F1: 0.3114
sub_4:Test (Best Model) - Loss: 7.6043 - Accuracy: 0.3571 - F1: 0.3314
sub_5:Test (Best Model) - Loss: 2.1192 - Accuracy: 0.3762 - F1: 0.3442
sub_6:Test (Best Model) - Loss: 8.4194 - Accuracy: 0.3762 - F1: 0.3388
sub_4:Test (Best Model) - Loss: 3.9922 - Accuracy: 0.3667 - F1: 0.3180
sub_5:Test (Best Model) - Loss: 2.7399 - Accuracy: 0.3762 - F1: 0.3500
sub_6:Test (Best Model) - Loss: 3.7679 - Accuracy: 0.3667 - F1: 0.3570
sub_4:Test (Best Model) - Loss: 2.7173 - Accuracy: 0.3619 - F1: 0.3326
sub_5:Test (Best Model) - Loss: 2.3382 - Accuracy: 0.3333 - F1: 0.3026
sub_4:Test (Best Model) - Loss: 3.0599 - Accuracy: 0.2905 - F1: 0.3049
sub_6:Test (Best Model) - Loss: 7.3370 - Accuracy: 0.3619 - F1: 0.3135
sub_5:Test (Best Model) - Loss: 3.6626 - Accuracy: 0.3762 - F1: 0.3252
sub_4:Test (Best Model) - Loss: 3.7228 - Accuracy: 0.3476 - F1: 0.3421
sub_6:Test (Best Model) - Loss: 7.8115 - Accuracy: 0.3286 - F1: 0.3019
sub_5:Test (Best Model) - Loss: 5.7911 - Accuracy: 0.2286 - F1: 0.2155
sub_4:Test (Best Model) - Loss: 3.3183 - Accuracy: 0.2857 - F1: 0.2906
sub_5:Test (Best Model) - Loss: 4.2109 - Accuracy: 0.2524 - F1: 0.2487
sub_6:Test (Best Model) - Loss: 7.5117 - Accuracy: 0.3333 - F1: 0.2725
sub_4:Test (Best Model) - Loss: 4.3617 - Accuracy: 0.3238 - F1: 0.3215
sub_6:Test (Best Model) - Loss: 5.9220 - Accuracy: 0.2714 - F1: 0.2290
sub_5:Test (Best Model) - Loss: 7.9059 - Accuracy: 0.2905 - F1: 0.2806
sub_6:Test (Best Model) - Loss: 7.5253 - Accuracy: 0.3143 - F1: 0.2853
sub_5:Test (Best Model) - Loss: 4.0266 - Accuracy: 0.2238 - F1: 0.2029
sub_5:Test (Best Model) - Loss: 3.8610 - Accuracy: 0.2667 - F1: 0.2591
sub_6:Test (Best Model) - Loss: 7.8963 - Accuracy: 0.3381 - F1: 0.2799
sub_6:Test (Best Model) - Loss: 3.0505 - Accuracy: 0.3810 - F1: 0.3342
sub_7:Test (Best Model) - Loss: 5.1480 - Accuracy: 0.3286 - F1: 0.3258
sub_9:Test (Best Model) - Loss: 7.0652 - Accuracy: 0.2952 - F1: 0.2077
sub_8:Test (Best Model) - Loss: 2.5274 - Accuracy: 0.4190 - F1: 0.4036
sub_9:Test (Best Model) - Loss: 10.4179 - Accuracy: 0.2476 - F1: 0.1474
sub_7:Test (Best Model) - Loss: 4.3309 - Accuracy: 0.3095 - F1: 0.3060
sub_8:Test (Best Model) - Loss: 3.0181 - Accuracy: 0.4429 - F1: 0.4077
sub_7:Test (Best Model) - Loss: 6.3344 - Accuracy: 0.2095 - F1: 0.1873
sub_9:Test (Best Model) - Loss: 5.5246 - Accuracy: 0.3190 - F1: 0.2584
sub_7:Test (Best Model) - Loss: 5.3789 - Accuracy: 0.2333 - F1: 0.2378
sub_8:Test (Best Model) - Loss: 5.0091 - Accuracy: 0.4476 - F1: 0.4353
sub_9:Test (Best Model) - Loss: 5.8061 - Accuracy: 0.3429 - F1: 0.2793
sub_7:Test (Best Model) - Loss: 5.4124 - Accuracy: 0.2905 - F1: 0.2823
sub_8:Test (Best Model) - Loss: 2.4889 - Accuracy: 0.4190 - F1: 0.3395
sub_9:Test (Best Model) - Loss: 4.6925 - Accuracy: 0.3333 - F1: 0.2388
sub_7:Test (Best Model) - Loss: 2.8889 - Accuracy: 0.3095 - F1: 0.2876
sub_8:Test (Best Model) - Loss: 3.4347 - Accuracy: 0.4190 - F1: 0.3779
sub_9:Test (Best Model) - Loss: 4.0482 - Accuracy: 0.4238 - F1: 0.3978
sub_8:Test (Best Model) - Loss: 2.1623 - Accuracy: 0.4762 - F1: 0.4725
sub_7:Test (Best Model) - Loss: 3.5399 - Accuracy: 0.3048 - F1: 0.2828
sub_8:Test (Best Model) - Loss: 1.8390 - Accuracy: 0.4857 - F1: 0.4566
sub_9:Test (Best Model) - Loss: 4.5346 - Accuracy: 0.4238 - F1: 0.3790
sub_8:Test (Best Model) - Loss: 1.7624 - Accuracy: 0.5143 - F1: 0.5104
sub_7:Test (Best Model) - Loss: 4.3725 - Accuracy: 0.3571 - F1: 0.3276
sub_9:Test (Best Model) - Loss: 8.9344 - Accuracy: 0.3762 - F1: 0.3143
sub_7:Test (Best Model) - Loss: 3.2129 - Accuracy: 0.3571 - F1: 0.3209
sub_8:Test (Best Model) - Loss: 2.6780 - Accuracy: 0.5190 - F1: 0.5090
sub_9:Test (Best Model) - Loss: 4.5188 - Accuracy: 0.3619 - F1: 0.3115
sub_8:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.5143 - F1: 0.5051
sub_8:Test (Best Model) - Loss: 4.5996 - Accuracy: 0.3952 - F1: 0.3786
sub_9:Test (Best Model) - Loss: 5.0368 - Accuracy: 0.3762 - F1: 0.3194
sub_7:Test (Best Model) - Loss: 4.2673 - Accuracy: 0.3143 - F1: 0.3035
sub_8:Test (Best Model) - Loss: 7.5639 - Accuracy: 0.3857 - F1: 0.3421
sub_9:Test (Best Model) - Loss: 5.8472 - Accuracy: 0.3571 - F1: 0.3424
sub_7:Test (Best Model) - Loss: 4.9484 - Accuracy: 0.3524 - F1: 0.3455
sub_8:Test (Best Model) - Loss: 9.8904 - Accuracy: 0.4190 - F1: 0.3671
sub_7:Test (Best Model) - Loss: 4.4432 - Accuracy: 0.3619 - F1: 0.3441
sub_9:Test (Best Model) - Loss: 7.3976 - Accuracy: 0.3143 - F1: 0.2702
sub_8:Test (Best Model) - Loss: 5.2497 - Accuracy: 0.4048 - F1: 0.3643
sub_9:Test (Best Model) - Loss: 5.2001 - Accuracy: 0.3286 - F1: 0.3059
sub_7:Test (Best Model) - Loss: 6.7728 - Accuracy: 0.3667 - F1: 0.3539
sub_8:Test (Best Model) - Loss: 5.2412 - Accuracy: 0.3857 - F1: 0.3465
sub_9:Test (Best Model) - Loss: 6.2423 - Accuracy: 0.3333 - F1: 0.3145
sub_7:Test (Best Model) - Loss: 3.9896 - Accuracy: 0.3714 - F1: 0.3496
sub_9:Test (Best Model) - Loss: 3.4735 - Accuracy: 0.3619 - F1: 0.3109
sub_7:Test (Best Model) - Loss: 3.3185 - Accuracy: 0.3714 - F1: 0.3478
sub_11:Test (Best Model) - Loss: 4.8213 - Accuracy: 0.3857 - F1: 0.3681
sub_10:Test (Best Model) - Loss: 4.1935 - Accuracy: 0.3952 - F1: 0.3705
sub_12:Test (Best Model) - Loss: 5.3319 - Accuracy: 0.3048 - F1: 0.3117
sub_10:Test (Best Model) - Loss: 4.0845 - Accuracy: 0.3619 - F1: 0.3356
sub_11:Test (Best Model) - Loss: 4.7907 - Accuracy: 0.3667 - F1: 0.3523
sub_12:Test (Best Model) - Loss: 3.1211 - Accuracy: 0.3429 - F1: 0.3487
sub_10:Test (Best Model) - Loss: 4.4662 - Accuracy: 0.4667 - F1: 0.4679
sub_10:Test (Best Model) - Loss: 3.3705 - Accuracy: 0.3714 - F1: 0.3504
sub_10:Test (Best Model) - Loss: 1.9763 - Accuracy: 0.4143 - F1: 0.3996
sub_11:Test (Best Model) - Loss: 7.1856 - Accuracy: 0.3667 - F1: 0.3407
sub_12:Test (Best Model) - Loss: 4.4367 - Accuracy: 0.3095 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 3.3578 - Accuracy: 0.3286 - F1: 0.3029
sub_11:Test (Best Model) - Loss: 3.6485 - Accuracy: 0.3667 - F1: 0.3362
sub_10:Test (Best Model) - Loss: 5.8175 - Accuracy: 0.3143 - F1: 0.2507
sub_12:Test (Best Model) - Loss: 3.1423 - Accuracy: 0.3857 - F1: 0.3653
sub_11:Test (Best Model) - Loss: 5.7858 - Accuracy: 0.3905 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 4.6398 - Accuracy: 0.3286 - F1: 0.2633
sub_12:Test (Best Model) - Loss: 2.7362 - Accuracy: 0.4000 - F1: 0.3683
sub_12:Test (Best Model) - Loss: 2.4301 - Accuracy: 0.3905 - F1: 0.3391
sub_11:Test (Best Model) - Loss: 6.0289 - Accuracy: 0.4000 - F1: 0.3695
sub_10:Test (Best Model) - Loss: 3.7805 - Accuracy: 0.3524 - F1: 0.2951
sub_12:Test (Best Model) - Loss: 4.2457 - Accuracy: 0.3857 - F1: 0.3404
sub_12:Test (Best Model) - Loss: 2.3265 - Accuracy: 0.4333 - F1: 0.4064
sub_10:Test (Best Model) - Loss: 5.1114 - Accuracy: 0.2952 - F1: 0.2256
sub_11:Test (Best Model) - Loss: 7.5594 - Accuracy: 0.4524 - F1: 0.4269
sub_10:Test (Best Model) - Loss: 2.5552 - Accuracy: 0.3381 - F1: 0.2609
sub_12:Test (Best Model) - Loss: 4.4771 - Accuracy: 0.4000 - F1: 0.3483
sub_12:Test (Best Model) - Loss: 9.7001 - Accuracy: 0.2714 - F1: 0.2480
sub_10:Test (Best Model) - Loss: 6.9397 - Accuracy: 0.2571 - F1: 0.2192
sub_11:Test (Best Model) - Loss: 5.6323 - Accuracy: 0.3762 - F1: 0.3905
sub_10:Test (Best Model) - Loss: 6.8083 - Accuracy: 0.2619 - F1: 0.2263
sub_12:Test (Best Model) - Loss: 13.1207 - Accuracy: 0.2905 - F1: 0.2265
sub_11:Test (Best Model) - Loss: 4.0282 - Accuracy: 0.4857 - F1: 0.4405
sub_10:Test (Best Model) - Loss: 4.4445 - Accuracy: 0.3095 - F1: 0.2592
sub_12:Test (Best Model) - Loss: 11.0097 - Accuracy: 0.2619 - F1: 0.2524
sub_11:Test (Best Model) - Loss: 4.7231 - Accuracy: 0.3857 - F1: 0.3722
sub_10:Test (Best Model) - Loss: 8.3649 - Accuracy: 0.2857 - F1: 0.2212
sub_12:Test (Best Model) - Loss: 11.6555 - Accuracy: 0.2905 - F1: 0.2462
sub_11:Test (Best Model) - Loss: 3.3305 - Accuracy: 0.4000 - F1: 0.3622
sub_10:Test (Best Model) - Loss: 3.5751 - Accuracy: 0.2762 - F1: 0.1903
sub_12:Test (Best Model) - Loss: 11.9795 - Accuracy: 0.3143 - F1: 0.2659
sub_11:Test (Best Model) - Loss: 4.0912 - Accuracy: 0.3952 - F1: 0.3854
sub_11:Test (Best Model) - Loss: 3.4273 - Accuracy: 0.4000 - F1: 0.3937
sub_11:Test (Best Model) - Loss: 4.0504 - Accuracy: 0.3762 - F1: 0.3601
sub_11:Test (Best Model) - Loss: 4.5970 - Accuracy: 0.4190 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 3.7210 - Accuracy: 0.3048 - F1: 0.2297
sub_13:Test (Best Model) - Loss: 2.6764 - Accuracy: 0.3619 - F1: 0.3033
sub_14:Test (Best Model) - Loss: 5.4166 - Accuracy: 0.4048 - F1: 0.4041
sub_13:Test (Best Model) - Loss: 6.6613 - Accuracy: 0.3286 - F1: 0.2205
sub_14:Test (Best Model) - Loss: 6.0613 - Accuracy: 0.3714 - F1: 0.3799
sub_14:Test (Best Model) - Loss: 2.2606 - Accuracy: 0.3952 - F1: 0.4005
sub_13:Test (Best Model) - Loss: 5.3088 - Accuracy: 0.2762 - F1: 0.1633
sub_14:Test (Best Model) - Loss: 4.2836 - Accuracy: 0.4000 - F1: 0.3922
sub_13:Test (Best Model) - Loss: 6.7127 - Accuracy: 0.2762 - F1: 0.1784
sub_14:Test (Best Model) - Loss: 2.2662 - Accuracy: 0.3762 - F1: 0.3765
sub_13:Test (Best Model) - Loss: 1.8690 - Accuracy: 0.3714 - F1: 0.3299
sub_13:Test (Best Model) - Loss: 2.3919 - Accuracy: 0.3762 - F1: 0.3507
sub_14:Test (Best Model) - Loss: 2.7268 - Accuracy: 0.4476 - F1: 0.4218
sub_13:Test (Best Model) - Loss: 2.7464 - Accuracy: 0.4143 - F1: 0.3939
sub_14:Test (Best Model) - Loss: 1.7482 - Accuracy: 0.4333 - F1: 0.4150
sub_13:Test (Best Model) - Loss: 2.3517 - Accuracy: 0.3476 - F1: 0.3460
sub_13:Test (Best Model) - Loss: 2.1345 - Accuracy: 0.3619 - F1: 0.3466
sub_13:Test (Best Model) - Loss: 4.0052 - Accuracy: 0.4476 - F1: 0.4066
sub_14:Test (Best Model) - Loss: 3.0379 - Accuracy: 0.4429 - F1: 0.4104
sub_13:Test (Best Model) - Loss: 3.0038 - Accuracy: 0.3810 - F1: 0.3306
sub_14:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.4714 - F1: 0.4619
sub_13:Test (Best Model) - Loss: 5.7126 - Accuracy: 0.3714 - F1: 0.3487
sub_14:Test (Best Model) - Loss: 1.3316 - Accuracy: 0.4810 - F1: 0.4375
sub_13:Test (Best Model) - Loss: 4.0548 - Accuracy: 0.4381 - F1: 0.3695
sub_14:Test (Best Model) - Loss: 3.0360 - Accuracy: 0.3667 - F1: 0.3189
sub_14:Test (Best Model) - Loss: 3.1136 - Accuracy: 0.2714 - F1: 0.2041
sub_13:Test (Best Model) - Loss: 4.5806 - Accuracy: 0.4238 - F1: 0.4197
sub_14:Test (Best Model) - Loss: 4.1037 - Accuracy: 0.3143 - F1: 0.2541
sub_14:Test (Best Model) - Loss: 2.9137 - Accuracy: 0.3048 - F1: 0.2542
sub_14:Test (Best Model) - Loss: 7.6566 - Accuracy: 0.3143 - F1: 0.2438

=== Summary Results ===

acc: 35.71 ± 3.27
F1: 32.24 ± 3.62
acc-in: 50.21 ± 3.41
F1-in: 47.63 ± 3.82
runing time: 2692.90 seconds
