lr: 0.001
sub_1:Test (Best Model) - Loss: 26.0131 - Accuracy: 0.2619 - F1: 0.1799
sub_1:Test (Best Model) - Loss: 13.8385 - Accuracy: 0.2810 - F1: 0.2258
sub_1:Test (Best Model) - Loss: 15.7115 - Accuracy: 0.3190 - F1: 0.2600
sub_1:Test (Best Model) - Loss: 11.3699 - Accuracy: 0.2762 - F1: 0.2253
sub_1:Test (Best Model) - Loss: 12.6465 - Accuracy: 0.3143 - F1: 0.2571
sub_1:Test (Best Model) - Loss: 10.0192 - Accuracy: 0.2952 - F1: 0.3011
sub_1:Test (Best Model) - Loss: 7.3746 - Accuracy: 0.3429 - F1: 0.3484
sub_1:Test (Best Model) - Loss: 14.0049 - Accuracy: 0.2762 - F1: 0.2774
sub_1:Test (Best Model) - Loss: 5.9557 - Accuracy: 0.3286 - F1: 0.3327
sub_1:Test (Best Model) - Loss: 12.3679 - Accuracy: 0.2571 - F1: 0.2634
sub_1:Test (Best Model) - Loss: 8.5471 - Accuracy: 0.3143 - F1: 0.3087
sub_1:Test (Best Model) - Loss: 10.4864 - Accuracy: 0.2238 - F1: 0.2175
sub_1:Test (Best Model) - Loss: 8.6451 - Accuracy: 0.2667 - F1: 0.2484
sub_1:Test (Best Model) - Loss: 8.7815 - Accuracy: 0.2667 - F1: 0.2583
sub_1:Test (Best Model) - Loss: 10.7379 - Accuracy: 0.2714 - F1: 0.2647
sub_2:Test (Best Model) - Loss: 10.4651 - Accuracy: 0.3429 - F1: 0.3107
sub_2:Test (Best Model) - Loss: 7.0972 - Accuracy: 0.3190 - F1: 0.2875
sub_2:Test (Best Model) - Loss: 7.7307 - Accuracy: 0.2952 - F1: 0.2891
sub_2:Test (Best Model) - Loss: 8.7955 - Accuracy: 0.3667 - F1: 0.2909
sub_2:Test (Best Model) - Loss: 7.4019 - Accuracy: 0.3571 - F1: 0.3299
sub_2:Test (Best Model) - Loss: 9.1691 - Accuracy: 0.3429 - F1: 0.3447
sub_2:Test (Best Model) - Loss: 8.7905 - Accuracy: 0.3476 - F1: 0.3531
sub_2:Test (Best Model) - Loss: 6.8069 - Accuracy: 0.3667 - F1: 0.3764
sub_2:Test (Best Model) - Loss: 8.7896 - Accuracy: 0.2952 - F1: 0.2934
sub_2:Test (Best Model) - Loss: 8.9103 - Accuracy: 0.2476 - F1: 0.2584
sub_2:Test (Best Model) - Loss: 8.3646 - Accuracy: 0.2857 - F1: 0.2909
sub_2:Test (Best Model) - Loss: 10.1530 - Accuracy: 0.2619 - F1: 0.2631
sub_2:Test (Best Model) - Loss: 8.0062 - Accuracy: 0.3000 - F1: 0.3014
sub_2:Test (Best Model) - Loss: 6.8631 - Accuracy: 0.3429 - F1: 0.3429
sub_2:Test (Best Model) - Loss: 7.5650 - Accuracy: 0.3238 - F1: 0.3334
sub_3:Test (Best Model) - Loss: 6.7493 - Accuracy: 0.2905 - F1: 0.2503
sub_3:Test (Best Model) - Loss: 10.1881 - Accuracy: 0.2381 - F1: 0.1935
sub_3:Test (Best Model) - Loss: 9.3692 - Accuracy: 0.2381 - F1: 0.1650
sub_3:Test (Best Model) - Loss: 8.4810 - Accuracy: 0.2571 - F1: 0.2210
sub_3:Test (Best Model) - Loss: 16.3335 - Accuracy: 0.2429 - F1: 0.1463
sub_3:Test (Best Model) - Loss: 7.5917 - Accuracy: 0.2667 - F1: 0.2663
sub_3:Test (Best Model) - Loss: 9.6237 - Accuracy: 0.2667 - F1: 0.2675
sub_3:Test (Best Model) - Loss: 8.8331 - Accuracy: 0.3333 - F1: 0.3026
sub_3:Test (Best Model) - Loss: 7.5824 - Accuracy: 0.2952 - F1: 0.2941
sub_3:Test (Best Model) - Loss: 8.5290 - Accuracy: 0.2952 - F1: 0.2981
sub_3:Test (Best Model) - Loss: 10.7925 - Accuracy: 0.2190 - F1: 0.2129
sub_3:Test (Best Model) - Loss: 11.0464 - Accuracy: 0.2238 - F1: 0.1985
sub_3:Test (Best Model) - Loss: 9.5648 - Accuracy: 0.2667 - F1: 0.2621
sub_3:Test (Best Model) - Loss: 8.6653 - Accuracy: 0.2190 - F1: 0.2225
sub_3:Test (Best Model) - Loss: 9.6903 - Accuracy: 0.2476 - F1: 0.2280
sub_4:Test (Best Model) - Loss: 8.9596 - Accuracy: 0.3286 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 8.7156 - Accuracy: 0.2762 - F1: 0.2663
sub_4:Test (Best Model) - Loss: 8.7169 - Accuracy: 0.2905 - F1: 0.2811
sub_4:Test (Best Model) - Loss: 7.6961 - Accuracy: 0.2619 - F1: 0.2564
sub_4:Test (Best Model) - Loss: 8.4419 - Accuracy: 0.2429 - F1: 0.2293
sub_4:Test (Best Model) - Loss: 13.7956 - Accuracy: 0.3286 - F1: 0.3210
sub_4:Test (Best Model) - Loss: 13.4663 - Accuracy: 0.2524 - F1: 0.2448
sub_4:Test (Best Model) - Loss: 12.3429 - Accuracy: 0.2476 - F1: 0.2503
sub_4:Test (Best Model) - Loss: 9.4616 - Accuracy: 0.2524 - F1: 0.2145
sub_4:Test (Best Model) - Loss: 9.1018 - Accuracy: 0.2857 - F1: 0.2781
sub_4:Test (Best Model) - Loss: 7.4743 - Accuracy: 0.3524 - F1: 0.3375
sub_4:Test (Best Model) - Loss: 8.2719 - Accuracy: 0.3714 - F1: 0.3375
sub_4:Test (Best Model) - Loss: 7.1840 - Accuracy: 0.3524 - F1: 0.2832
sub_4:Test (Best Model) - Loss: 7.3133 - Accuracy: 0.3524 - F1: 0.3344
sub_4:Test (Best Model) - Loss: 9.6892 - Accuracy: 0.3619 - F1: 0.3517
sub_5:Test (Best Model) - Loss: 10.2749 - Accuracy: 0.3000 - F1: 0.2563
sub_5:Test (Best Model) - Loss: 12.3168 - Accuracy: 0.3095 - F1: 0.2490
sub_5:Test (Best Model) - Loss: 13.2747 - Accuracy: 0.3857 - F1: 0.3348
sub_5:Test (Best Model) - Loss: 16.5549 - Accuracy: 0.3143 - F1: 0.2560
sub_5:Test (Best Model) - Loss: 9.7398 - Accuracy: 0.3762 - F1: 0.2992
sub_5:Test (Best Model) - Loss: 11.7843 - Accuracy: 0.3333 - F1: 0.3347
sub_5:Test (Best Model) - Loss: 7.9717 - Accuracy: 0.3000 - F1: 0.3063
sub_5:Test (Best Model) - Loss: 7.2459 - Accuracy: 0.3857 - F1: 0.3844
sub_5:Test (Best Model) - Loss: 8.8644 - Accuracy: 0.3048 - F1: 0.3128
sub_5:Test (Best Model) - Loss: 10.3915 - Accuracy: 0.3190 - F1: 0.3072
sub_5:Test (Best Model) - Loss: 10.3888 - Accuracy: 0.2619 - F1: 0.2630
sub_5:Test (Best Model) - Loss: 11.2040 - Accuracy: 0.3190 - F1: 0.3369
sub_5:Test (Best Model) - Loss: 8.2746 - Accuracy: 0.3048 - F1: 0.3157
sub_5:Test (Best Model) - Loss: 8.8949 - Accuracy: 0.2476 - F1: 0.2523
sub_5:Test (Best Model) - Loss: 7.0814 - Accuracy: 0.2810 - F1: 0.2951
sub_6:Test (Best Model) - Loss: 8.9701 - Accuracy: 0.2524 - F1: 0.2535
sub_6:Test (Best Model) - Loss: 9.4809 - Accuracy: 0.2905 - F1: 0.2956
sub_6:Test (Best Model) - Loss: 9.0904 - Accuracy: 0.2524 - F1: 0.2376
sub_6:Test (Best Model) - Loss: 10.5344 - Accuracy: 0.2429 - F1: 0.2464
sub_6:Test (Best Model) - Loss: 7.1663 - Accuracy: 0.3381 - F1: 0.3284
sub_6:Test (Best Model) - Loss: 10.6764 - Accuracy: 0.2381 - F1: 0.2406
sub_6:Test (Best Model) - Loss: 11.3460 - Accuracy: 0.2571 - F1: 0.2412
sub_6:Test (Best Model) - Loss: 9.2613 - Accuracy: 0.2429 - F1: 0.2307
sub_6:Test (Best Model) - Loss: 10.3331 - Accuracy: 0.2381 - F1: 0.2337
sub_6:Test (Best Model) - Loss: 10.6103 - Accuracy: 0.2952 - F1: 0.2664
sub_6:Test (Best Model) - Loss: 7.8097 - Accuracy: 0.2619 - F1: 0.2493
sub_6:Test (Best Model) - Loss: 7.8254 - Accuracy: 0.3048 - F1: 0.2917
sub_6:Test (Best Model) - Loss: 7.7764 - Accuracy: 0.2857 - F1: 0.2831
sub_6:Test (Best Model) - Loss: 7.1858 - Accuracy: 0.2571 - F1: 0.2510
sub_6:Test (Best Model) - Loss: 9.3532 - Accuracy: 0.2857 - F1: 0.2842
sub_7:Test (Best Model) - Loss: 8.7557 - Accuracy: 0.2571 - F1: 0.2489
sub_7:Test (Best Model) - Loss: 10.4367 - Accuracy: 0.2667 - F1: 0.2487
sub_7:Test (Best Model) - Loss: 10.0276 - Accuracy: 0.2429 - F1: 0.2092
sub_7:Test (Best Model) - Loss: 8.4008 - Accuracy: 0.1952 - F1: 0.1871
sub_7:Test (Best Model) - Loss: 10.8607 - Accuracy: 0.2524 - F1: 0.2163
sub_7:Test (Best Model) - Loss: 9.5693 - Accuracy: 0.2571 - F1: 0.2558
sub_7:Test (Best Model) - Loss: 9.2708 - Accuracy: 0.2143 - F1: 0.2096
sub_7:Test (Best Model) - Loss: 11.2468 - Accuracy: 0.2095 - F1: 0.1958
sub_7:Test (Best Model) - Loss: 8.0806 - Accuracy: 0.2238 - F1: 0.2139
sub_7:Test (Best Model) - Loss: 10.5913 - Accuracy: 0.2048 - F1: 0.1971
sub_7:Test (Best Model) - Loss: 8.1901 - Accuracy: 0.2190 - F1: 0.2170
sub_7:Test (Best Model) - Loss: 6.9562 - Accuracy: 0.2000 - F1: 0.1987
sub_7:Test (Best Model) - Loss: 10.5289 - Accuracy: 0.2095 - F1: 0.1782
sub_7:Test (Best Model) - Loss: 7.0508 - Accuracy: 0.1762 - F1: 0.1724
sub_7:Test (Best Model) - Loss: 7.8453 - Accuracy: 0.2667 - F1: 0.2632
sub_8:Test (Best Model) - Loss: 11.6987 - Accuracy: 0.3476 - F1: 0.3074
sub_8:Test (Best Model) - Loss: 7.4499 - Accuracy: 0.3619 - F1: 0.3328
sub_8:Test (Best Model) - Loss: 9.4567 - Accuracy: 0.3476 - F1: 0.3139
sub_8:Test (Best Model) - Loss: 10.7664 - Accuracy: 0.3286 - F1: 0.3142
sub_8:Test (Best Model) - Loss: 8.5997 - Accuracy: 0.3524 - F1: 0.3231
sub_8:Test (Best Model) - Loss: 7.6238 - Accuracy: 0.3095 - F1: 0.3141
sub_8:Test (Best Model) - Loss: 9.4523 - Accuracy: 0.2857 - F1: 0.3002
sub_8:Test (Best Model) - Loss: 9.1889 - Accuracy: 0.3524 - F1: 0.3623
sub_8:Test (Best Model) - Loss: 7.9728 - Accuracy: 0.2857 - F1: 0.3022
sub_8:Test (Best Model) - Loss: 8.7361 - Accuracy: 0.3476 - F1: 0.3579
sub_8:Test (Best Model) - Loss: 9.3464 - Accuracy: 0.3048 - F1: 0.3133
sub_8:Test (Best Model) - Loss: 9.8562 - Accuracy: 0.2429 - F1: 0.2519
sub_8:Test (Best Model) - Loss: 10.5483 - Accuracy: 0.3333 - F1: 0.3303
sub_8:Test (Best Model) - Loss: 7.5401 - Accuracy: 0.3714 - F1: 0.3483
sub_8:Test (Best Model) - Loss: 9.6882 - Accuracy: 0.3476 - F1: 0.3538
sub_9:Test (Best Model) - Loss: 11.0555 - Accuracy: 0.2952 - F1: 0.2443
sub_9:Test (Best Model) - Loss: 8.3221 - Accuracy: 0.2762 - F1: 0.2402
sub_9:Test (Best Model) - Loss: 12.4709 - Accuracy: 0.3238 - F1: 0.2870
sub_9:Test (Best Model) - Loss: 15.2800 - Accuracy: 0.2762 - F1: 0.1937
sub_9:Test (Best Model) - Loss: 10.5131 - Accuracy: 0.3000 - F1: 0.2645
sub_9:Test (Best Model) - Loss: 9.0962 - Accuracy: 0.3048 - F1: 0.2895
sub_9:Test (Best Model) - Loss: 8.2612 - Accuracy: 0.3095 - F1: 0.2931
sub_9:Test (Best Model) - Loss: 10.2432 - Accuracy: 0.1857 - F1: 0.1787
sub_9:Test (Best Model) - Loss: 6.7314 - Accuracy: 0.3381 - F1: 0.3205
sub_9:Test (Best Model) - Loss: 9.7662 - Accuracy: 0.2810 - F1: 0.2697
sub_9:Test (Best Model) - Loss: 9.9357 - Accuracy: 0.2667 - F1: 0.2794
sub_9:Test (Best Model) - Loss: 8.3408 - Accuracy: 0.2810 - F1: 0.2721
sub_9:Test (Best Model) - Loss: 7.8861 - Accuracy: 0.3524 - F1: 0.3482
sub_9:Test (Best Model) - Loss: 6.2464 - Accuracy: 0.3143 - F1: 0.3239
sub_9:Test (Best Model) - Loss: 8.3580 - Accuracy: 0.3238 - F1: 0.3372
sub_10:Test (Best Model) - Loss: 7.6182 - Accuracy: 0.2952 - F1: 0.2903
sub_10:Test (Best Model) - Loss: 6.9214 - Accuracy: 0.2952 - F1: 0.2816
sub_10:Test (Best Model) - Loss: 9.3947 - Accuracy: 0.2905 - F1: 0.2845
sub_10:Test (Best Model) - Loss: 7.2344 - Accuracy: 0.3048 - F1: 0.2775
sub_10:Test (Best Model) - Loss: 7.2894 - Accuracy: 0.2619 - F1: 0.2568
sub_10:Test (Best Model) - Loss: 8.6567 - Accuracy: 0.2571 - F1: 0.2507
sub_10:Test (Best Model) - Loss: 8.8307 - Accuracy: 0.2143 - F1: 0.2104
sub_10:Test (Best Model) - Loss: 7.1076 - Accuracy: 0.2667 - F1: 0.2595
sub_10:Test (Best Model) - Loss: 7.3562 - Accuracy: 0.2714 - F1: 0.2686
sub_10:Test (Best Model) - Loss: 8.3566 - Accuracy: 0.2762 - F1: 0.2432
sub_10:Test (Best Model) - Loss: 9.0615 - Accuracy: 0.2238 - F1: 0.2196
sub_10:Test (Best Model) - Loss: 8.4593 - Accuracy: 0.2905 - F1: 0.2894
sub_10:Test (Best Model) - Loss: 7.7389 - Accuracy: 0.3095 - F1: 0.3081
sub_10:Test (Best Model) - Loss: 9.1877 - Accuracy: 0.2524 - F1: 0.2411
sub_10:Test (Best Model) - Loss: 10.7509 - Accuracy: 0.2190 - F1: 0.2043
sub_11:Test (Best Model) - Loss: 10.3468 - Accuracy: 0.2333 - F1: 0.2220
sub_11:Test (Best Model) - Loss: 9.2877 - Accuracy: 0.2286 - F1: 0.2224
sub_11:Test (Best Model) - Loss: 9.7911 - Accuracy: 0.2667 - F1: 0.2465
sub_11:Test (Best Model) - Loss: 10.4499 - Accuracy: 0.2381 - F1: 0.2028
sub_11:Test (Best Model) - Loss: 8.6571 - Accuracy: 0.2476 - F1: 0.2477
sub_11:Test (Best Model) - Loss: 8.8748 - Accuracy: 0.2476 - F1: 0.2516
sub_11:Test (Best Model) - Loss: 7.8016 - Accuracy: 0.2476 - F1: 0.2562
sub_11:Test (Best Model) - Loss: 5.9994 - Accuracy: 0.2952 - F1: 0.3011
sub_11:Test (Best Model) - Loss: 8.5397 - Accuracy: 0.2667 - F1: 0.2564
sub_11:Test (Best Model) - Loss: 7.1302 - Accuracy: 0.2857 - F1: 0.2920
sub_11:Test (Best Model) - Loss: 8.3357 - Accuracy: 0.2667 - F1: 0.2657
sub_11:Test (Best Model) - Loss: 7.8660 - Accuracy: 0.3429 - F1: 0.3288
sub_11:Test (Best Model) - Loss: 8.8380 - Accuracy: 0.2810 - F1: 0.2930
sub_11:Test (Best Model) - Loss: 7.6004 - Accuracy: 0.2952 - F1: 0.2927
sub_11:Test (Best Model) - Loss: 8.2093 - Accuracy: 0.2857 - F1: 0.2849
sub_12:Test (Best Model) - Loss: 7.4677 - Accuracy: 0.3714 - F1: 0.3738
sub_12:Test (Best Model) - Loss: 8.4656 - Accuracy: 0.2619 - F1: 0.2693
sub_12:Test (Best Model) - Loss: 8.4522 - Accuracy: 0.3857 - F1: 0.3872
sub_12:Test (Best Model) - Loss: 9.4049 - Accuracy: 0.3667 - F1: 0.3731
sub_12:Test (Best Model) - Loss: 7.2142 - Accuracy: 0.2714 - F1: 0.2837
sub_12:Test (Best Model) - Loss: 10.5774 - Accuracy: 0.3095 - F1: 0.2548
sub_12:Test (Best Model) - Loss: 10.2652 - Accuracy: 0.2762 - F1: 0.2325
sub_12:Test (Best Model) - Loss: 10.5465 - Accuracy: 0.3286 - F1: 0.2810
sub_12:Test (Best Model) - Loss: 13.0503 - Accuracy: 0.2905 - F1: 0.2263
sub_12:Test (Best Model) - Loss: 11.5117 - Accuracy: 0.3000 - F1: 0.2470
sub_12:Test (Best Model) - Loss: 11.3650 - Accuracy: 0.2048 - F1: 0.2095
sub_12:Test (Best Model) - Loss: 12.6370 - Accuracy: 0.2238 - F1: 0.2283
sub_12:Test (Best Model) - Loss: 10.2153 - Accuracy: 0.2762 - F1: 0.2880
sub_12:Test (Best Model) - Loss: 11.8729 - Accuracy: 0.2429 - F1: 0.2510
sub_12:Test (Best Model) - Loss: 12.3709 - Accuracy: 0.2286 - F1: 0.2327
sub_13:Test (Best Model) - Loss: 7.2736 - Accuracy: 0.2905 - F1: 0.2760
sub_13:Test (Best Model) - Loss: 7.8950 - Accuracy: 0.2476 - F1: 0.2316
sub_13:Test (Best Model) - Loss: 8.6927 - Accuracy: 0.2810 - F1: 0.2463
sub_13:Test (Best Model) - Loss: 8.5079 - Accuracy: 0.2952 - F1: 0.2894
sub_13:Test (Best Model) - Loss: 16.1207 - Accuracy: 0.2286 - F1: 0.1539
sub_13:Test (Best Model) - Loss: 10.0684 - Accuracy: 0.2571 - F1: 0.2504
sub_13:Test (Best Model) - Loss: 9.0226 - Accuracy: 0.2238 - F1: 0.2281
sub_13:Test (Best Model) - Loss: 8.2836 - Accuracy: 0.2476 - F1: 0.2387
sub_13:Test (Best Model) - Loss: 9.7881 - Accuracy: 0.2286 - F1: 0.2326
sub_13:Test (Best Model) - Loss: 9.4084 - Accuracy: 0.2810 - F1: 0.2693
sub_13:Test (Best Model) - Loss: 9.3655 - Accuracy: 0.2429 - F1: 0.2267
sub_13:Test (Best Model) - Loss: 10.8520 - Accuracy: 0.2667 - F1: 0.2471
sub_13:Test (Best Model) - Loss: 9.0474 - Accuracy: 0.2429 - F1: 0.1969
sub_13:Test (Best Model) - Loss: 6.2291 - Accuracy: 0.2857 - F1: 0.2470
sub_13:Test (Best Model) - Loss: 9.3611 - Accuracy: 0.2667 - F1: 0.2519
sub_14:Test (Best Model) - Loss: 7.9325 - Accuracy: 0.3238 - F1: 0.3442
sub_14:Test (Best Model) - Loss: 11.0157 - Accuracy: 0.3238 - F1: 0.3388
sub_14:Test (Best Model) - Loss: 9.0593 - Accuracy: 0.3286 - F1: 0.3360
sub_14:Test (Best Model) - Loss: 9.5981 - Accuracy: 0.3095 - F1: 0.3138
sub_14:Test (Best Model) - Loss: 15.2432 - Accuracy: 0.2286 - F1: 0.2328
sub_14:Test (Best Model) - Loss: 8.0680 - Accuracy: 0.3095 - F1: 0.3109
sub_14:Test (Best Model) - Loss: 8.3237 - Accuracy: 0.3857 - F1: 0.3604
sub_14:Test (Best Model) - Loss: 8.5376 - Accuracy: 0.3524 - F1: 0.3397
sub_14:Test (Best Model) - Loss: 12.7256 - Accuracy: 0.3238 - F1: 0.3065
sub_14:Test (Best Model) - Loss: 9.6538 - Accuracy: 0.3095 - F1: 0.2806
sub_14:Test (Best Model) - Loss: 9.9579 - Accuracy: 0.3143 - F1: 0.2923
sub_14:Test (Best Model) - Loss: 7.8947 - Accuracy: 0.3190 - F1: 0.3159
sub_14:Test (Best Model) - Loss: 7.5766 - Accuracy: 0.3190 - F1: 0.3177
sub_14:Test (Best Model) - Loss: 12.6364 - Accuracy: 0.3429 - F1: 0.3186
sub_14:Test (Best Model) - Loss: 8.5158 - Accuracy: 0.3238 - F1: 0.3085

=== Summary Results ===

acc: 28.65 ± 2.84
F1: 27.32 ± 3.05
acc-in: 35.92 ± 3.91
F1-in: 33.76 ± 4.05
