lr: 1e-06
sub_7:Test (Best Model) - Loss: 1.7667 - Accuracy: 0.1952 - F1: 0.1642
sub_13:Test (Best Model) - Loss: 1.6750 - Accuracy: 0.2571 - F1: 0.2194
sub_4:Test (Best Model) - Loss: 1.7723 - Accuracy: 0.1952 - F1: 0.1858
sub_5:Test (Best Model) - Loss: 1.6589 - Accuracy: 0.2143 - F1: 0.1893
sub_10:Test (Best Model) - Loss: 1.7110 - Accuracy: 0.1571 - F1: 0.1420
sub_2:Test (Best Model) - Loss: 1.6854 - Accuracy: 0.2714 - F1: 0.2571
sub_1:Test (Best Model) - Loss: 1.6385 - Accuracy: 0.2762 - F1: 0.2518
sub_6:Test (Best Model) - Loss: 1.8098 - Accuracy: 0.1286 - F1: 0.1231
sub_14:Test (Best Model) - Loss: 1.6932 - Accuracy: 0.2238 - F1: 0.2104
sub_7:Test (Best Model) - Loss: 1.6852 - Accuracy: 0.2238 - F1: 0.2155
sub_13:Test (Best Model) - Loss: 1.8829 - Accuracy: 0.2000 - F1: 0.1359
sub_10:Test (Best Model) - Loss: 1.7451 - Accuracy: 0.1381 - F1: 0.1299
sub_2:Test (Best Model) - Loss: 1.8332 - Accuracy: 0.1952 - F1: 0.1609
sub_3:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2714 - F1: 0.2475
sub_9:Test (Best Model) - Loss: 1.7144 - Accuracy: 0.2905 - F1: 0.1823
sub_11:Test (Best Model) - Loss: 1.6658 - Accuracy: 0.2619 - F1: 0.2226
sub_12:Test (Best Model) - Loss: 1.6577 - Accuracy: 0.2714 - F1: 0.2213
sub_7:Test (Best Model) - Loss: 1.8282 - Accuracy: 0.1810 - F1: 0.1560
sub_6:Test (Best Model) - Loss: 1.7191 - Accuracy: 0.1619 - F1: 0.1414
sub_14:Test (Best Model) - Loss: 1.6959 - Accuracy: 0.1857 - F1: 0.1585
sub_8:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.3000 - F1: 0.2454
sub_13:Test (Best Model) - Loss: 1.8383 - Accuracy: 0.2143 - F1: 0.1599
sub_10:Test (Best Model) - Loss: 1.8274 - Accuracy: 0.2571 - F1: 0.2277
sub_4:Test (Best Model) - Loss: 1.6849 - Accuracy: 0.2143 - F1: 0.1981
sub_2:Test (Best Model) - Loss: 1.9376 - Accuracy: 0.1238 - F1: 0.0964
sub_9:Test (Best Model) - Loss: 1.7544 - Accuracy: 0.1810 - F1: 0.1231
sub_3:Test (Best Model) - Loss: 1.8342 - Accuracy: 0.2524 - F1: 0.1804
sub_5:Test (Best Model) - Loss: 1.7845 - Accuracy: 0.1429 - F1: 0.1224
sub_12:Test (Best Model) - Loss: 1.6407 - Accuracy: 0.2381 - F1: 0.2276
sub_7:Test (Best Model) - Loss: 1.6935 - Accuracy: 0.2190 - F1: 0.1798
sub_6:Test (Best Model) - Loss: 1.8283 - Accuracy: 0.1905 - F1: 0.1412
sub_14:Test (Best Model) - Loss: 1.8031 - Accuracy: 0.2190 - F1: 0.1845
sub_4:Test (Best Model) - Loss: 1.8377 - Accuracy: 0.2143 - F1: 0.1816
sub_9:Test (Best Model) - Loss: 1.8712 - Accuracy: 0.1429 - F1: 0.0994
sub_5:Test (Best Model) - Loss: 1.8703 - Accuracy: 0.1714 - F1: 0.1342
sub_12:Test (Best Model) - Loss: 1.9044 - Accuracy: 0.1619 - F1: 0.1414
sub_10:Test (Best Model) - Loss: 1.7957 - Accuracy: 0.2238 - F1: 0.1423
sub_3:Test (Best Model) - Loss: 1.7888 - Accuracy: 0.2095 - F1: 0.1317
sub_1:Test (Best Model) - Loss: 1.6452 - Accuracy: 0.2048 - F1: 0.2037
sub_8:Test (Best Model) - Loss: 1.7594 - Accuracy: 0.1905 - F1: 0.1728
sub_11:Test (Best Model) - Loss: 1.7829 - Accuracy: 0.1714 - F1: 0.1442
sub_5:Test (Best Model) - Loss: 1.7460 - Accuracy: 0.1905 - F1: 0.1588
sub_7:Test (Best Model) - Loss: 1.6975 - Accuracy: 0.1905 - F1: 0.1624
sub_13:Test (Best Model) - Loss: 1.8631 - Accuracy: 0.1571 - F1: 0.1072
sub_10:Test (Best Model) - Loss: 1.5881 - Accuracy: 0.2762 - F1: 0.2567
sub_3:Test (Best Model) - Loss: 1.7846 - Accuracy: 0.2952 - F1: 0.2010
sub_8:Test (Best Model) - Loss: 1.8213 - Accuracy: 0.1762 - F1: 0.1340
sub_2:Test (Best Model) - Loss: 1.6947 - Accuracy: 0.2238 - F1: 0.1676
sub_6:Test (Best Model) - Loss: 1.7340 - Accuracy: 0.2048 - F1: 0.1609
sub_1:Test (Best Model) - Loss: 1.7982 - Accuracy: 0.2762 - F1: 0.1971
sub_7:Test (Best Model) - Loss: 1.7557 - Accuracy: 0.2333 - F1: 0.1802
sub_11:Test (Best Model) - Loss: 1.7162 - Accuracy: 0.2333 - F1: 0.1983
sub_10:Test (Best Model) - Loss: 1.7045 - Accuracy: 0.2048 - F1: 0.1537
sub_5:Test (Best Model) - Loss: 1.6421 - Accuracy: 0.2095 - F1: 0.1750
sub_6:Test (Best Model) - Loss: 1.7504 - Accuracy: 0.1762 - F1: 0.1432
sub_9:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.3571 - F1: 0.2361
sub_7:Test (Best Model) - Loss: 1.7627 - Accuracy: 0.2143 - F1: 0.1468
sub_4:Test (Best Model) - Loss: 1.5808 - Accuracy: 0.3095 - F1: 0.2952
sub_3:Test (Best Model) - Loss: 1.6676 - Accuracy: 0.2714 - F1: 0.2184
sub_12:Test (Best Model) - Loss: 1.6909 - Accuracy: 0.2857 - F1: 0.2252
sub_14:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.3190 - F1: 0.2712
sub_2:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2905 - F1: 0.2223
sub_10:Test (Best Model) - Loss: 1.6745 - Accuracy: 0.2571 - F1: 0.2281
sub_8:Test (Best Model) - Loss: 1.6736 - Accuracy: 0.2810 - F1: 0.1910
sub_9:Test (Best Model) - Loss: 1.7269 - Accuracy: 0.2143 - F1: 0.1503
sub_7:Test (Best Model) - Loss: 1.7278 - Accuracy: 0.2381 - F1: 0.1777
sub_6:Test (Best Model) - Loss: 1.7105 - Accuracy: 0.2429 - F1: 0.2044
sub_3:Test (Best Model) - Loss: 1.7393 - Accuracy: 0.1762 - F1: 0.1437
sub_5:Test (Best Model) - Loss: 1.7168 - Accuracy: 0.1905 - F1: 0.1725
sub_10:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.2667 - F1: 0.2371
sub_13:Test (Best Model) - Loss: 1.7365 - Accuracy: 0.1810 - F1: 0.1444
sub_1:Test (Best Model) - Loss: 1.8093 - Accuracy: 0.1905 - F1: 0.1492
sub_11:Test (Best Model) - Loss: 1.6771 - Accuracy: 0.2190 - F1: 0.1542
sub_2:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2429 - F1: 0.2183
sub_7:Test (Best Model) - Loss: 1.7822 - Accuracy: 0.1762 - F1: 0.1426
sub_6:Test (Best Model) - Loss: 1.7981 - Accuracy: 0.2238 - F1: 0.1852
sub_1:Test (Best Model) - Loss: 1.6879 - Accuracy: 0.1905 - F1: 0.1697
sub_11:Test (Best Model) - Loss: 1.6355 - Accuracy: 0.2571 - F1: 0.2168
sub_7:Test (Best Model) - Loss: 1.7472 - Accuracy: 0.1762 - F1: 0.1629
sub_6:Test (Best Model) - Loss: 1.7549 - Accuracy: 0.2095 - F1: 0.1563
sub_9:Test (Best Model) - Loss: 1.6522 - Accuracy: 0.2000 - F1: 0.1972
sub_4:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2333 - F1: 0.2227
sub_3:Test (Best Model) - Loss: 1.8268 - Accuracy: 0.1571 - F1: 0.0971
sub_2:Test (Best Model) - Loss: 1.7552 - Accuracy: 0.2000 - F1: 0.1928
sub_14:Test (Best Model) - Loss: 1.6759 - Accuracy: 0.2048 - F1: 0.2031
sub_5:Test (Best Model) - Loss: 1.7848 - Accuracy: 0.2048 - F1: 0.1748
sub_13:Test (Best Model) - Loss: 1.7246 - Accuracy: 0.1952 - F1: 0.1404
sub_7:Test (Best Model) - Loss: 1.8741 - Accuracy: 0.2048 - F1: 0.1073
sub_8:Test (Best Model) - Loss: 1.4985 - Accuracy: 0.3667 - F1: 0.3382
sub_10:Test (Best Model) - Loss: 1.7569 - Accuracy: 0.2524 - F1: 0.2301
sub_12:Test (Best Model) - Loss: 1.5752 - Accuracy: 0.2857 - F1: 0.2370
sub_11:Test (Best Model) - Loss: 1.6886 - Accuracy: 0.2333 - F1: 0.2093
sub_6:Test (Best Model) - Loss: 1.7404 - Accuracy: 0.1762 - F1: 0.1600
sub_5:Test (Best Model) - Loss: 1.8188 - Accuracy: 0.1810 - F1: 0.1178
sub_1:Test (Best Model) - Loss: 1.6549 - Accuracy: 0.2429 - F1: 0.2052
sub_13:Test (Best Model) - Loss: 1.7021 - Accuracy: 0.2333 - F1: 0.1820
sub_7:Test (Best Model) - Loss: 1.7580 - Accuracy: 0.2143 - F1: 0.1850
sub_4:Test (Best Model) - Loss: 1.7494 - Accuracy: 0.2048 - F1: 0.1776
sub_6:Test (Best Model) - Loss: 1.6146 - Accuracy: 0.2571 - F1: 0.2213
sub_2:Test (Best Model) - Loss: 1.6853 - Accuracy: 0.2381 - F1: 0.1909
sub_5:Test (Best Model) - Loss: 1.7242 - Accuracy: 0.1810 - F1: 0.1713
sub_13:Test (Best Model) - Loss: 1.7540 - Accuracy: 0.1952 - F1: 0.1429
sub_1:Test (Best Model) - Loss: 1.7616 - Accuracy: 0.2143 - F1: 0.1657
sub_10:Test (Best Model) - Loss: 1.6900 - Accuracy: 0.1952 - F1: 0.1826
sub_3:Test (Best Model) - Loss: 1.6646 - Accuracy: 0.1952 - F1: 0.1794
sub_11:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.3000 - F1: 0.2594
sub_9:Test (Best Model) - Loss: 1.7281 - Accuracy: 0.2905 - F1: 0.2558
sub_8:Test (Best Model) - Loss: 1.6925 - Accuracy: 0.2476 - F1: 0.2228
sub_4:Test (Best Model) - Loss: 1.7978 - Accuracy: 0.1571 - F1: 0.1329
sub_6:Test (Best Model) - Loss: 1.7957 - Accuracy: 0.2381 - F1: 0.2086
sub_7:Test (Best Model) - Loss: 1.7517 - Accuracy: 0.2143 - F1: 0.1618
sub_5:Test (Best Model) - Loss: 1.6966 - Accuracy: 0.2048 - F1: 0.1729
sub_12:Test (Best Model) - Loss: 1.7165 - Accuracy: 0.1714 - F1: 0.1539
sub_13:Test (Best Model) - Loss: 1.7133 - Accuracy: 0.1952 - F1: 0.1855
sub_1:Test (Best Model) - Loss: 1.6928 - Accuracy: 0.2429 - F1: 0.1886
sub_14:Test (Best Model) - Loss: 1.7324 - Accuracy: 0.2190 - F1: 0.1644
sub_10:Test (Best Model) - Loss: 1.6984 - Accuracy: 0.2190 - F1: 0.1745
sub_3:Test (Best Model) - Loss: 1.7172 - Accuracy: 0.1810 - F1: 0.1712
sub_9:Test (Best Model) - Loss: 1.7475 - Accuracy: 0.1571 - F1: 0.1409
sub_7:Test (Best Model) - Loss: 1.7250 - Accuracy: 0.1952 - F1: 0.1795
sub_5:Test (Best Model) - Loss: 1.7686 - Accuracy: 0.2048 - F1: 0.1707
sub_4:Test (Best Model) - Loss: 1.7022 - Accuracy: 0.2333 - F1: 0.1657
sub_1:Test (Best Model) - Loss: 1.6747 - Accuracy: 0.2381 - F1: 0.2079
sub_2:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2381 - F1: 0.2139
sub_8:Test (Best Model) - Loss: 1.5668 - Accuracy: 0.2952 - F1: 0.2785
sub_6:Test (Best Model) - Loss: 1.7511 - Accuracy: 0.1762 - F1: 0.1361
sub_5:Test (Best Model) - Loss: 1.7179 - Accuracy: 0.2333 - F1: 0.2102
sub_4:Test (Best Model) - Loss: 1.7402 - Accuracy: 0.2238 - F1: 0.1807
sub_1:Test (Best Model) - Loss: 1.5734 - Accuracy: 0.2429 - F1: 0.2207
sub_11:Test (Best Model) - Loss: 1.5896 - Accuracy: 0.2857 - F1: 0.2517
sub_14:Test (Best Model) - Loss: 1.7635 - Accuracy: 0.2476 - F1: 0.2441
sub_13:Test (Best Model) - Loss: 1.6411 - Accuracy: 0.2190 - F1: 0.2121
sub_12:Test (Best Model) - Loss: 1.7384 - Accuracy: 0.2000 - F1: 0.1779
sub_9:Test (Best Model) - Loss: 1.7597 - Accuracy: 0.2095 - F1: 0.1554
sub_3:Test (Best Model) - Loss: 1.6403 - Accuracy: 0.2714 - F1: 0.2732
sub_2:Test (Best Model) - Loss: 1.6312 - Accuracy: 0.2190 - F1: 0.1913
sub_7:Test (Best Model) - Loss: 1.6857 - Accuracy: 0.2190 - F1: 0.2038
sub_4:Test (Best Model) - Loss: 1.6456 - Accuracy: 0.2667 - F1: 0.2266
sub_1:Test (Best Model) - Loss: 1.8859 - Accuracy: 0.2048 - F1: 0.1486
sub_10:Test (Best Model) - Loss: 1.9190 - Accuracy: 0.2000 - F1: 0.1335
sub_14:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.2762 - F1: 0.2674
sub_3:Test (Best Model) - Loss: 1.9370 - Accuracy: 0.1857 - F1: 0.1036
sub_9:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.2381 - F1: 0.2277
sub_12:Test (Best Model) - Loss: 1.7111 - Accuracy: 0.2286 - F1: 0.2084
sub_4:Test (Best Model) - Loss: 1.8425 - Accuracy: 0.1762 - F1: 0.1322
sub_14:Test (Best Model) - Loss: 1.5885 - Accuracy: 0.2762 - F1: 0.2612
sub_5:Test (Best Model) - Loss: 1.6845 - Accuracy: 0.2048 - F1: 0.1856
sub_9:Test (Best Model) - Loss: 1.8890 - Accuracy: 0.2000 - F1: 0.0970
sub_13:Test (Best Model) - Loss: 1.7130 - Accuracy: 0.1810 - F1: 0.1487
sub_2:Test (Best Model) - Loss: 1.6151 - Accuracy: 0.2857 - F1: 0.2490
sub_3:Test (Best Model) - Loss: 1.6672 - Accuracy: 0.2333 - F1: 0.2185
sub_8:Test (Best Model) - Loss: 1.5094 - Accuracy: 0.3381 - F1: 0.3250
sub_5:Test (Best Model) - Loss: 1.7508 - Accuracy: 0.2048 - F1: 0.1604
sub_13:Test (Best Model) - Loss: 1.8365 - Accuracy: 0.2048 - F1: 0.1480
sub_9:Test (Best Model) - Loss: 1.7211 - Accuracy: 0.1952 - F1: 0.1654
sub_4:Test (Best Model) - Loss: 1.7939 - Accuracy: 0.2048 - F1: 0.1776
sub_6:Test (Best Model) - Loss: 1.6233 - Accuracy: 0.3286 - F1: 0.2896
sub_14:Test (Best Model) - Loss: 1.7199 - Accuracy: 0.2333 - F1: 0.1946
sub_11:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2048 - F1: 0.1948
sub_10:Test (Best Model) - Loss: 1.8077 - Accuracy: 0.1905 - F1: 0.1286
sub_2:Test (Best Model) - Loss: 1.7264 - Accuracy: 0.2333 - F1: 0.1984
sub_12:Test (Best Model) - Loss: 1.7597 - Accuracy: 0.2381 - F1: 0.2011
sub_13:Test (Best Model) - Loss: 1.6966 - Accuracy: 0.2238 - F1: 0.1706
sub_4:Test (Best Model) - Loss: 1.8279 - Accuracy: 0.2190 - F1: 0.1855
sub_14:Test (Best Model) - Loss: 1.8748 - Accuracy: 0.1905 - F1: 0.1099
sub_10:Test (Best Model) - Loss: 1.6679 - Accuracy: 0.1952 - F1: 0.1458
sub_5:Test (Best Model) - Loss: 1.6699 - Accuracy: 0.2667 - F1: 0.2244
sub_3:Test (Best Model) - Loss: 1.6575 - Accuracy: 0.2333 - F1: 0.2102
sub_13:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.2429 - F1: 0.2313
sub_12:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.3190 - F1: 0.3060
sub_4:Test (Best Model) - Loss: 1.7378 - Accuracy: 0.2286 - F1: 0.2052
sub_14:Test (Best Model) - Loss: 1.7083 - Accuracy: 0.2571 - F1: 0.2496
sub_8:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2476 - F1: 0.2448
sub_1:Test (Best Model) - Loss: 1.5412 - Accuracy: 0.3333 - F1: 0.3124
sub_3:Test (Best Model) - Loss: 1.6643 - Accuracy: 0.2333 - F1: 0.2090
sub_9:Test (Best Model) - Loss: 1.6759 - Accuracy: 0.2524 - F1: 0.2133
sub_11:Test (Best Model) - Loss: 1.4453 - Accuracy: 0.3857 - F1: 0.3813
sub_6:Test (Best Model) - Loss: 1.6685 - Accuracy: 0.2190 - F1: 0.2091
sub_14:Test (Best Model) - Loss: 1.9106 - Accuracy: 0.1333 - F1: 0.1145
sub_8:Test (Best Model) - Loss: 1.6651 - Accuracy: 0.2429 - F1: 0.2223
sub_2:Test (Best Model) - Loss: 1.6486 - Accuracy: 0.1857 - F1: 0.1790
sub_3:Test (Best Model) - Loss: 1.6986 - Accuracy: 0.2429 - F1: 0.1848
sub_11:Test (Best Model) - Loss: 1.8234 - Accuracy: 0.2381 - F1: 0.1955
sub_9:Test (Best Model) - Loss: 1.5692 - Accuracy: 0.2857 - F1: 0.2723
sub_1:Test (Best Model) - Loss: 1.6572 - Accuracy: 0.2095 - F1: 0.1793
sub_10:Test (Best Model) - Loss: 1.6875 - Accuracy: 0.2429 - F1: 0.1479
sub_6:Test (Best Model) - Loss: 1.5944 - Accuracy: 0.3238 - F1: 0.2928
sub_14:Test (Best Model) - Loss: 1.7509 - Accuracy: 0.1762 - F1: 0.1480
sub_8:Test (Best Model) - Loss: 2.0856 - Accuracy: 0.2048 - F1: 0.1529
sub_13:Test (Best Model) - Loss: 1.5736 - Accuracy: 0.3048 - F1: 0.2570
sub_2:Test (Best Model) - Loss: 1.7628 - Accuracy: 0.1857 - F1: 0.1563
sub_1:Test (Best Model) - Loss: 1.6016 - Accuracy: 0.2286 - F1: 0.2213
sub_9:Test (Best Model) - Loss: 1.5794 - Accuracy: 0.2810 - F1: 0.2537
sub_4:Test (Best Model) - Loss: 1.6483 - Accuracy: 0.3000 - F1: 0.2726
sub_12:Test (Best Model) - Loss: 1.6676 - Accuracy: 0.2476 - F1: 0.2045
sub_1:Test (Best Model) - Loss: 1.7044 - Accuracy: 0.1905 - F1: 0.1606
sub_11:Test (Best Model) - Loss: 1.5147 - Accuracy: 0.3762 - F1: 0.3505
sub_2:Test (Best Model) - Loss: 1.6623 - Accuracy: 0.2571 - F1: 0.1863
sub_12:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2429 - F1: 0.2222
sub_14:Test (Best Model) - Loss: 1.6735 - Accuracy: 0.1952 - F1: 0.1686
sub_8:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2905 - F1: 0.2567
sub_11:Test (Best Model) - Loss: 1.7153 - Accuracy: 0.2667 - F1: 0.2160
sub_11:Test (Best Model) - Loss: 1.6997 - Accuracy: 0.1810 - F1: 0.1627
sub_12:Test (Best Model) - Loss: 1.6266 - Accuracy: 0.2952 - F1: 0.2399
sub_8:Test (Best Model) - Loss: 1.6418 - Accuracy: 0.2619 - F1: 0.2157
sub_11:Test (Best Model) - Loss: 1.4493 - Accuracy: 0.3952 - F1: 0.3747
sub_12:Test (Best Model) - Loss: 1.5630 - Accuracy: 0.2619 - F1: 0.2450
sub_8:Test (Best Model) - Loss: 1.5904 - Accuracy: 0.2238 - F1: 0.2152
sub_12:Test (Best Model) - Loss: 1.6404 - Accuracy: 0.3000 - F1: 0.1962
sub_8:Test (Best Model) - Loss: 1.5966 - Accuracy: 0.2952 - F1: 0.2683

=== Summary Results ===

acc: 22.89 ± 1.90
F1: 19.33 ± 2.05
acc-in: 26.50 ± 2.96
F1-in: 23.41 ± 3.15
