lr: 0.0001
sub_1:Test (Best Model) - Loss: 2.1893 - Accuracy: 0.2714 - F1: 0.2440
sub_1:Test (Best Model) - Loss: 2.0493 - Accuracy: 0.3000 - F1: 0.2580
sub_1:Test (Best Model) - Loss: 1.8921 - Accuracy: 0.2619 - F1: 0.2210
sub_1:Test (Best Model) - Loss: 2.2871 - Accuracy: 0.2714 - F1: 0.2228
sub_1:Test (Best Model) - Loss: 1.9322 - Accuracy: 0.2762 - F1: 0.2439
sub_1:Test (Best Model) - Loss: 1.8749 - Accuracy: 0.3000 - F1: 0.3032
sub_1:Test (Best Model) - Loss: 1.7490 - Accuracy: 0.3238 - F1: 0.3291
sub_1:Test (Best Model) - Loss: 1.8135 - Accuracy: 0.3429 - F1: 0.3465
sub_1:Test (Best Model) - Loss: 1.7645 - Accuracy: 0.3143 - F1: 0.3209
sub_1:Test (Best Model) - Loss: 1.8756 - Accuracy: 0.3143 - F1: 0.3232
sub_1:Test (Best Model) - Loss: 2.0654 - Accuracy: 0.2857 - F1: 0.2931
sub_1:Test (Best Model) - Loss: 2.3275 - Accuracy: 0.2857 - F1: 0.2927
sub_1:Test (Best Model) - Loss: 1.7788 - Accuracy: 0.3000 - F1: 0.3047
sub_1:Test (Best Model) - Loss: 2.0930 - Accuracy: 0.2524 - F1: 0.2550
sub_1:Test (Best Model) - Loss: 1.9104 - Accuracy: 0.2762 - F1: 0.2799
sub_2:Test (Best Model) - Loss: 1.9857 - Accuracy: 0.2810 - F1: 0.2715
sub_2:Test (Best Model) - Loss: 2.1564 - Accuracy: 0.3095 - F1: 0.2992
sub_2:Test (Best Model) - Loss: 2.0803 - Accuracy: 0.2762 - F1: 0.2653
sub_2:Test (Best Model) - Loss: 2.2250 - Accuracy: 0.2619 - F1: 0.2402
sub_2:Test (Best Model) - Loss: 1.8008 - Accuracy: 0.2571 - F1: 0.2442
sub_2:Test (Best Model) - Loss: 2.3442 - Accuracy: 0.2810 - F1: 0.2821
sub_2:Test (Best Model) - Loss: 2.0078 - Accuracy: 0.2095 - F1: 0.2101
sub_2:Test (Best Model) - Loss: 1.8819 - Accuracy: 0.2714 - F1: 0.2662
sub_2:Test (Best Model) - Loss: 2.0220 - Accuracy: 0.2571 - F1: 0.2546
sub_2:Test (Best Model) - Loss: 1.9566 - Accuracy: 0.2238 - F1: 0.2264
sub_2:Test (Best Model) - Loss: 2.0109 - Accuracy: 0.2905 - F1: 0.2922
sub_2:Test (Best Model) - Loss: 2.3442 - Accuracy: 0.2476 - F1: 0.2516
sub_2:Test (Best Model) - Loss: 2.2631 - Accuracy: 0.2429 - F1: 0.2473
sub_2:Test (Best Model) - Loss: 2.1341 - Accuracy: 0.2286 - F1: 0.2338
sub_2:Test (Best Model) - Loss: 2.7473 - Accuracy: 0.2810 - F1: 0.2805
sub_3:Test (Best Model) - Loss: 1.8053 - Accuracy: 0.2429 - F1: 0.2219
sub_3:Test (Best Model) - Loss: 1.9720 - Accuracy: 0.2810 - F1: 0.2310
sub_3:Test (Best Model) - Loss: 2.2893 - Accuracy: 0.3095 - F1: 0.2674
sub_3:Test (Best Model) - Loss: 2.0926 - Accuracy: 0.2762 - F1: 0.2321
sub_3:Test (Best Model) - Loss: 1.8692 - Accuracy: 0.2810 - F1: 0.2333
sub_3:Test (Best Model) - Loss: 2.2063 - Accuracy: 0.2762 - F1: 0.2805
sub_3:Test (Best Model) - Loss: 1.7569 - Accuracy: 0.2667 - F1: 0.2637
sub_3:Test (Best Model) - Loss: 1.7635 - Accuracy: 0.2714 - F1: 0.2709
sub_3:Test (Best Model) - Loss: 1.8430 - Accuracy: 0.2762 - F1: 0.2719
sub_3:Test (Best Model) - Loss: 1.9435 - Accuracy: 0.2714 - F1: 0.2689
sub_3:Test (Best Model) - Loss: 1.7936 - Accuracy: 0.2762 - F1: 0.2769
sub_3:Test (Best Model) - Loss: 1.9948 - Accuracy: 0.2333 - F1: 0.2311
sub_3:Test (Best Model) - Loss: 2.4847 - Accuracy: 0.2619 - F1: 0.2422
sub_3:Test (Best Model) - Loss: 2.0185 - Accuracy: 0.2381 - F1: 0.2342
sub_3:Test (Best Model) - Loss: 1.9036 - Accuracy: 0.2333 - F1: 0.2364
sub_4:Test (Best Model) - Loss: 2.1530 - Accuracy: 0.2143 - F1: 0.2084
sub_4:Test (Best Model) - Loss: 2.1892 - Accuracy: 0.1905 - F1: 0.1895
sub_4:Test (Best Model) - Loss: 2.7351 - Accuracy: 0.1905 - F1: 0.1861
sub_4:Test (Best Model) - Loss: 2.1634 - Accuracy: 0.2000 - F1: 0.1982
sub_4:Test (Best Model) - Loss: 2.6685 - Accuracy: 0.2286 - F1: 0.2271
sub_4:Test (Best Model) - Loss: 2.1241 - Accuracy: 0.2429 - F1: 0.2409
sub_4:Test (Best Model) - Loss: 2.0246 - Accuracy: 0.2238 - F1: 0.2249
sub_4:Test (Best Model) - Loss: 2.0484 - Accuracy: 0.2143 - F1: 0.2189
sub_4:Test (Best Model) - Loss: 2.4207 - Accuracy: 0.2810 - F1: 0.2808
sub_4:Test (Best Model) - Loss: 2.3670 - Accuracy: 0.2762 - F1: 0.2749
sub_4:Test (Best Model) - Loss: 2.1408 - Accuracy: 0.2190 - F1: 0.2197
sub_4:Test (Best Model) - Loss: 1.9621 - Accuracy: 0.1952 - F1: 0.1926
sub_4:Test (Best Model) - Loss: 2.0303 - Accuracy: 0.1952 - F1: 0.1885
sub_4:Test (Best Model) - Loss: 2.2252 - Accuracy: 0.2286 - F1: 0.2276
sub_4:Test (Best Model) - Loss: 1.9093 - Accuracy: 0.2000 - F1: 0.2001
sub_5:Test (Best Model) - Loss: 1.9419 - Accuracy: 0.2762 - F1: 0.2775
sub_5:Test (Best Model) - Loss: 2.5324 - Accuracy: 0.2810 - F1: 0.2726
sub_5:Test (Best Model) - Loss: 1.7872 - Accuracy: 0.3524 - F1: 0.3501
sub_5:Test (Best Model) - Loss: 2.0796 - Accuracy: 0.2952 - F1: 0.2875
sub_5:Test (Best Model) - Loss: 2.3534 - Accuracy: 0.2429 - F1: 0.2383
sub_5:Test (Best Model) - Loss: 2.3308 - Accuracy: 0.2571 - F1: 0.2609
sub_5:Test (Best Model) - Loss: 1.9829 - Accuracy: 0.2190 - F1: 0.2200
sub_5:Test (Best Model) - Loss: 2.1874 - Accuracy: 0.2476 - F1: 0.2507
sub_5:Test (Best Model) - Loss: 1.9794 - Accuracy: 0.2571 - F1: 0.2582
sub_5:Test (Best Model) - Loss: 1.9179 - Accuracy: 0.2238 - F1: 0.2235
sub_5:Test (Best Model) - Loss: 1.8568 - Accuracy: 0.2476 - F1: 0.2497
sub_5:Test (Best Model) - Loss: 1.8392 - Accuracy: 0.2810 - F1: 0.2839
sub_5:Test (Best Model) - Loss: 2.0200 - Accuracy: 0.2381 - F1: 0.2378
sub_5:Test (Best Model) - Loss: 1.8394 - Accuracy: 0.2095 - F1: 0.2119
sub_5:Test (Best Model) - Loss: 2.2481 - Accuracy: 0.2333 - F1: 0.2404
sub_6:Test (Best Model) - Loss: 2.2819 - Accuracy: 0.2000 - F1: 0.1956
sub_6:Test (Best Model) - Loss: 2.0599 - Accuracy: 0.2048 - F1: 0.2049
sub_6:Test (Best Model) - Loss: 2.2741 - Accuracy: 0.1905 - F1: 0.1913
sub_6:Test (Best Model) - Loss: 2.0135 - Accuracy: 0.2190 - F1: 0.2159
sub_6:Test (Best Model) - Loss: 2.1489 - Accuracy: 0.2048 - F1: 0.2002
sub_6:Test (Best Model) - Loss: 2.4458 - Accuracy: 0.2143 - F1: 0.2114
sub_6:Test (Best Model) - Loss: 2.4057 - Accuracy: 0.1714 - F1: 0.1712
sub_6:Test (Best Model) - Loss: 2.1055 - Accuracy: 0.1810 - F1: 0.1802
sub_6:Test (Best Model) - Loss: 2.1256 - Accuracy: 0.1857 - F1: 0.1827
sub_6:Test (Best Model) - Loss: 2.0166 - Accuracy: 0.1905 - F1: 0.1884
sub_6:Test (Best Model) - Loss: 2.0536 - Accuracy: 0.2333 - F1: 0.2322
sub_6:Test (Best Model) - Loss: 2.2470 - Accuracy: 0.2048 - F1: 0.2050
sub_6:Test (Best Model) - Loss: 1.9419 - Accuracy: 0.2857 - F1: 0.2830
sub_6:Test (Best Model) - Loss: 1.9290 - Accuracy: 0.2190 - F1: 0.2186
sub_6:Test (Best Model) - Loss: 2.4172 - Accuracy: 0.2429 - F1: 0.2422
sub_7:Test (Best Model) - Loss: 2.1545 - Accuracy: 0.2238 - F1: 0.2235
sub_7:Test (Best Model) - Loss: 2.1345 - Accuracy: 0.2429 - F1: 0.2374
sub_7:Test (Best Model) - Loss: 1.9146 - Accuracy: 0.2190 - F1: 0.2163
sub_7:Test (Best Model) - Loss: 2.0374 - Accuracy: 0.2143 - F1: 0.2122
sub_7:Test (Best Model) - Loss: 1.9505 - Accuracy: 0.2190 - F1: 0.2113
sub_7:Test (Best Model) - Loss: 1.9907 - Accuracy: 0.2000 - F1: 0.2008
sub_7:Test (Best Model) - Loss: 2.4018 - Accuracy: 0.2190 - F1: 0.2226
sub_7:Test (Best Model) - Loss: 1.9756 - Accuracy: 0.2048 - F1: 0.2089
sub_7:Test (Best Model) - Loss: 1.8774 - Accuracy: 0.2048 - F1: 0.2054
sub_7:Test (Best Model) - Loss: 2.0433 - Accuracy: 0.1905 - F1: 0.1900
sub_7:Test (Best Model) - Loss: 2.2098 - Accuracy: 0.2571 - F1: 0.2598
sub_7:Test (Best Model) - Loss: 2.4751 - Accuracy: 0.2333 - F1: 0.2333
sub_7:Test (Best Model) - Loss: 1.8858 - Accuracy: 0.2429 - F1: 0.2401
sub_7:Test (Best Model) - Loss: 2.1111 - Accuracy: 0.2143 - F1: 0.2122
sub_7:Test (Best Model) - Loss: 1.8161 - Accuracy: 0.1952 - F1: 0.1939
sub_8:Test (Best Model) - Loss: 2.0892 - Accuracy: 0.3476 - F1: 0.3444
sub_8:Test (Best Model) - Loss: 2.2123 - Accuracy: 0.3286 - F1: 0.3227
sub_8:Test (Best Model) - Loss: 1.6754 - Accuracy: 0.3048 - F1: 0.3013
sub_8:Test (Best Model) - Loss: 2.3543 - Accuracy: 0.3000 - F1: 0.2964
sub_8:Test (Best Model) - Loss: 2.0050 - Accuracy: 0.3286 - F1: 0.3218
sub_8:Test (Best Model) - Loss: 1.9501 - Accuracy: 0.3190 - F1: 0.3252
sub_8:Test (Best Model) - Loss: 1.9580 - Accuracy: 0.2667 - F1: 0.2787
sub_8:Test (Best Model) - Loss: 1.9117 - Accuracy: 0.3381 - F1: 0.3523
sub_8:Test (Best Model) - Loss: 2.2372 - Accuracy: 0.3238 - F1: 0.3403
sub_8:Test (Best Model) - Loss: 1.9864 - Accuracy: 0.3048 - F1: 0.3148
sub_8:Test (Best Model) - Loss: 2.3495 - Accuracy: 0.2810 - F1: 0.2956
sub_8:Test (Best Model) - Loss: 2.0234 - Accuracy: 0.2619 - F1: 0.2740
sub_8:Test (Best Model) - Loss: 1.9914 - Accuracy: 0.2524 - F1: 0.2675
sub_8:Test (Best Model) - Loss: 1.8233 - Accuracy: 0.2476 - F1: 0.2552
sub_8:Test (Best Model) - Loss: 3.0634 - Accuracy: 0.2714 - F1: 0.2875
sub_9:Test (Best Model) - Loss: 2.6019 - Accuracy: 0.2048 - F1: 0.2020
sub_9:Test (Best Model) - Loss: 2.0660 - Accuracy: 0.2333 - F1: 0.2331
sub_9:Test (Best Model) - Loss: 1.9664 - Accuracy: 0.2476 - F1: 0.2471
sub_9:Test (Best Model) - Loss: 2.4147 - Accuracy: 0.2190 - F1: 0.2118
sub_9:Test (Best Model) - Loss: 2.3832 - Accuracy: 0.2333 - F1: 0.2342
sub_9:Test (Best Model) - Loss: 2.4921 - Accuracy: 0.2333 - F1: 0.2352
sub_9:Test (Best Model) - Loss: 2.4348 - Accuracy: 0.2000 - F1: 0.2014
sub_9:Test (Best Model) - Loss: 2.1797 - Accuracy: 0.2000 - F1: 0.1988
sub_9:Test (Best Model) - Loss: 2.5378 - Accuracy: 0.2762 - F1: 0.2701
sub_9:Test (Best Model) - Loss: 2.0905 - Accuracy: 0.2381 - F1: 0.2320
sub_9:Test (Best Model) - Loss: 2.1977 - Accuracy: 0.2095 - F1: 0.2115
sub_9:Test (Best Model) - Loss: 1.9462 - Accuracy: 0.2333 - F1: 0.2326
sub_9:Test (Best Model) - Loss: 2.1589 - Accuracy: 0.2571 - F1: 0.2612
sub_9:Test (Best Model) - Loss: 1.9518 - Accuracy: 0.2048 - F1: 0.2028
sub_9:Test (Best Model) - Loss: 1.9023 - Accuracy: 0.2429 - F1: 0.2486
sub_10:Test (Best Model) - Loss: 2.0856 - Accuracy: 0.1952 - F1: 0.1883
sub_10:Test (Best Model) - Loss: 2.1728 - Accuracy: 0.2571 - F1: 0.2482
sub_10:Test (Best Model) - Loss: 2.3027 - Accuracy: 0.2143 - F1: 0.2065
sub_10:Test (Best Model) - Loss: 2.0718 - Accuracy: 0.1952 - F1: 0.1889
sub_10:Test (Best Model) - Loss: 1.9437 - Accuracy: 0.2000 - F1: 0.1952
sub_10:Test (Best Model) - Loss: 1.9092 - Accuracy: 0.2095 - F1: 0.2055
sub_10:Test (Best Model) - Loss: 1.9443 - Accuracy: 0.2429 - F1: 0.2409
sub_10:Test (Best Model) - Loss: 1.9001 - Accuracy: 0.2524 - F1: 0.2493
sub_10:Test (Best Model) - Loss: 2.1670 - Accuracy: 0.2524 - F1: 0.2529
sub_10:Test (Best Model) - Loss: 2.0135 - Accuracy: 0.2000 - F1: 0.2002
sub_10:Test (Best Model) - Loss: 2.2154 - Accuracy: 0.2429 - F1: 0.2389
sub_10:Test (Best Model) - Loss: 2.0379 - Accuracy: 0.2619 - F1: 0.2612
sub_10:Test (Best Model) - Loss: 2.1311 - Accuracy: 0.2524 - F1: 0.2473
sub_10:Test (Best Model) - Loss: 2.4866 - Accuracy: 0.2238 - F1: 0.2239
sub_10:Test (Best Model) - Loss: 2.1155 - Accuracy: 0.2238 - F1: 0.2241
sub_11:Test (Best Model) - Loss: 2.9775 - Accuracy: 0.2238 - F1: 0.2214
sub_11:Test (Best Model) - Loss: 2.4625 - Accuracy: 0.2000 - F1: 0.1986
sub_11:Test (Best Model) - Loss: 2.1481 - Accuracy: 0.1905 - F1: 0.1896
sub_11:Test (Best Model) - Loss: 2.4237 - Accuracy: 0.1762 - F1: 0.1734
sub_11:Test (Best Model) - Loss: 2.5594 - Accuracy: 0.2000 - F1: 0.1980
sub_11:Test (Best Model) - Loss: 1.9296 - Accuracy: 0.2476 - F1: 0.2483
sub_11:Test (Best Model) - Loss: 1.9382 - Accuracy: 0.2476 - F1: 0.2469
sub_11:Test (Best Model) - Loss: 1.8529 - Accuracy: 0.2714 - F1: 0.2720
sub_11:Test (Best Model) - Loss: 2.2014 - Accuracy: 0.2619 - F1: 0.2641
sub_11:Test (Best Model) - Loss: 2.0706 - Accuracy: 0.2762 - F1: 0.2760
sub_11:Test (Best Model) - Loss: 1.8710 - Accuracy: 0.2571 - F1: 0.2527
sub_11:Test (Best Model) - Loss: 2.1488 - Accuracy: 0.2857 - F1: 0.2842
sub_11:Test (Best Model) - Loss: 2.4988 - Accuracy: 0.2667 - F1: 0.2663
sub_11:Test (Best Model) - Loss: 2.0148 - Accuracy: 0.2714 - F1: 0.2713
sub_11:Test (Best Model) - Loss: 1.9325 - Accuracy: 0.2619 - F1: 0.2583
sub_12:Test (Best Model) - Loss: 1.8807 - Accuracy: 0.2048 - F1: 0.2119
sub_12:Test (Best Model) - Loss: 1.8883 - Accuracy: 0.1952 - F1: 0.1961
sub_12:Test (Best Model) - Loss: 1.8791 - Accuracy: 0.3095 - F1: 0.3084
sub_12:Test (Best Model) - Loss: 1.9451 - Accuracy: 0.3000 - F1: 0.3060
sub_12:Test (Best Model) - Loss: 1.9180 - Accuracy: 0.2095 - F1: 0.2146
sub_12:Test (Best Model) - Loss: 2.7389 - Accuracy: 0.2905 - F1: 0.2555
sub_12:Test (Best Model) - Loss: 2.3300 - Accuracy: 0.2238 - F1: 0.1937
sub_12:Test (Best Model) - Loss: 2.5975 - Accuracy: 0.2905 - F1: 0.2519
sub_12:Test (Best Model) - Loss: 1.7836 - Accuracy: 0.2714 - F1: 0.2504
sub_12:Test (Best Model) - Loss: 2.5599 - Accuracy: 0.3000 - F1: 0.2637
sub_12:Test (Best Model) - Loss: 2.3025 - Accuracy: 0.2095 - F1: 0.2107
sub_12:Test (Best Model) - Loss: 2.3146 - Accuracy: 0.2286 - F1: 0.2338
sub_12:Test (Best Model) - Loss: 2.2460 - Accuracy: 0.2238 - F1: 0.2287
sub_12:Test (Best Model) - Loss: 2.8251 - Accuracy: 0.2238 - F1: 0.2292
sub_12:Test (Best Model) - Loss: 3.1813 - Accuracy: 0.2143 - F1: 0.2194
sub_13:Test (Best Model) - Loss: 2.3325 - Accuracy: 0.2476 - F1: 0.2515
sub_13:Test (Best Model) - Loss: 2.2821 - Accuracy: 0.1905 - F1: 0.1907
sub_13:Test (Best Model) - Loss: 2.6615 - Accuracy: 0.2286 - F1: 0.2269
sub_13:Test (Best Model) - Loss: 1.8853 - Accuracy: 0.2048 - F1: 0.2077
sub_13:Test (Best Model) - Loss: 2.5421 - Accuracy: 0.2190 - F1: 0.2195
sub_13:Test (Best Model) - Loss: 2.9588 - Accuracy: 0.2238 - F1: 0.2241
sub_13:Test (Best Model) - Loss: 2.3178 - Accuracy: 0.2286 - F1: 0.2285
sub_13:Test (Best Model) - Loss: 1.9622 - Accuracy: 0.2238 - F1: 0.2198
sub_13:Test (Best Model) - Loss: 2.2986 - Accuracy: 0.2571 - F1: 0.2570
sub_13:Test (Best Model) - Loss: 2.7417 - Accuracy: 0.2524 - F1: 0.2543
sub_13:Test (Best Model) - Loss: 1.9767 - Accuracy: 0.2429 - F1: 0.2433
sub_13:Test (Best Model) - Loss: 2.2484 - Accuracy: 0.2429 - F1: 0.2414
sub_13:Test (Best Model) - Loss: 2.0553 - Accuracy: 0.2667 - F1: 0.2632
sub_13:Test (Best Model) - Loss: 1.8073 - Accuracy: 0.2381 - F1: 0.2335
sub_13:Test (Best Model) - Loss: 2.0115 - Accuracy: 0.2048 - F1: 0.2050
sub_14:Test (Best Model) - Loss: 2.1526 - Accuracy: 0.2571 - F1: 0.2647
sub_14:Test (Best Model) - Loss: 2.1131 - Accuracy: 0.2238 - F1: 0.2248
sub_14:Test (Best Model) - Loss: 2.0852 - Accuracy: 0.2762 - F1: 0.2789
sub_14:Test (Best Model) - Loss: 2.4597 - Accuracy: 0.2429 - F1: 0.2421
sub_14:Test (Best Model) - Loss: 2.1087 - Accuracy: 0.2143 - F1: 0.2123
sub_14:Test (Best Model) - Loss: 2.0957 - Accuracy: 0.3048 - F1: 0.3024
sub_14:Test (Best Model) - Loss: 1.9135 - Accuracy: 0.2524 - F1: 0.2506
sub_14:Test (Best Model) - Loss: 1.9408 - Accuracy: 0.2667 - F1: 0.2618
sub_14:Test (Best Model) - Loss: 1.9926 - Accuracy: 0.2810 - F1: 0.2809
sub_14:Test (Best Model) - Loss: 1.9105 - Accuracy: 0.1952 - F1: 0.1928
sub_14:Test (Best Model) - Loss: 2.0086 - Accuracy: 0.2905 - F1: 0.2878
sub_14:Test (Best Model) - Loss: 2.0547 - Accuracy: 0.2429 - F1: 0.2342
sub_14:Test (Best Model) - Loss: 2.1052 - Accuracy: 0.2476 - F1: 0.2439
sub_14:Test (Best Model) - Loss: 2.2616 - Accuracy: 0.2095 - F1: 0.2059
sub_14:Test (Best Model) - Loss: 2.1208 - Accuracy: 0.2714 - F1: 0.2612

=== Summary Results ===

acc: 24.66 ± 2.56
F1: 24.37 ± 2.55
acc-in: 29.22 ± 2.18
F1-in: 28.92 ± 2.31
