generated_from_trainer

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vit-small_tobacco3482_hint_

This model is a fine-tuned version of WinKawaks/vit-small-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Accuracy Brier Loss Nll F1 Micro F1 Macro Ece Aurc
No log 1.0 25 59.9015 0.37 0.7765 4.3056 0.37 0.2185 0.2975 0.4588
No log 2.0 50 58.9173 0.66 0.4866 2.0758 0.66 0.5717 0.2732 0.1578
No log 3.0 75 58.3604 0.745 0.3466 1.5077 0.745 0.7135 0.1846 0.0854
No log 4.0 100 58.0585 0.75 0.3628 1.5044 0.75 0.7674 0.2058 0.1052
No log 5.0 125 57.8363 0.76 0.3782 1.7066 0.76 0.7657 0.2174 0.1039
No log 6.0 150 57.4894 0.75 0.3593 1.5137 0.75 0.7377 0.1724 0.0800
No log 7.0 175 57.5188 0.76 0.3631 1.9770 0.76 0.7514 0.1968 0.0874
No log 8.0 200 57.4349 0.74 0.3947 1.8766 0.74 0.7412 0.1753 0.0777
No log 9.0 225 57.1764 0.765 0.3481 1.1532 0.765 0.7411 0.1956 0.0829
No log 10.0 250 57.6192 0.765 0.3943 1.8998 0.765 0.7755 0.1850 0.0981
No log 11.0 275 57.2121 0.77 0.3531 1.2685 0.7700 0.7643 0.1739 0.0689
No log 12.0 300 57.2250 0.795 0.3279 1.7553 0.795 0.7816 0.1596 0.0660
No log 13.0 325 57.4911 0.785 0.3678 2.0499 0.785 0.7857 0.1788 0.0945
No log 14.0 350 57.1481 0.77 0.3542 1.4834 0.7700 0.7649 0.1892 0.0636
No log 15.0 375 57.1701 0.825 0.3041 1.6075 0.825 0.8223 0.1609 0.0621
No log 16.0 400 57.4059 0.805 0.3343 1.7348 0.805 0.8080 0.1654 0.0822
No log 17.0 425 57.9813 0.72 0.4616 2.6345 0.72 0.7252 0.2263 0.1101
No log 18.0 450 57.2677 0.825 0.2953 1.5836 0.825 0.8171 0.1590 0.0572
No log 19.0 475 57.6052 0.765 0.4023 1.7463 0.765 0.7333 0.2052 0.0822
57.2084 20.0 500 57.4249 0.79 0.3653 1.5564 0.79 0.7941 0.1818 0.0845
57.2084 21.0 525 57.2631 0.845 0.2704 1.7326 0.845 0.8312 0.1358 0.0628
57.2084 22.0 550 57.1520 0.845 0.2723 1.2743 0.845 0.8386 0.1402 0.0551
57.2084 23.0 575 57.2977 0.82 0.3137 1.3068 0.82 0.8029 0.1578 0.0621
57.2084 24.0 600 57.2030 0.81 0.3107 1.5814 0.81 0.7870 0.1594 0.0688
57.2084 25.0 625 57.1500 0.82 0.3027 1.4128 0.82 0.8229 0.1584 0.0436
57.2084 26.0 650 57.1619 0.855 0.2735 1.5164 0.855 0.8558 0.1404 0.0530
57.2084 27.0 675 57.1504 0.845 0.2832 1.5742 0.845 0.8507 0.1500 0.0516
57.2084 28.0 700 57.1829 0.835 0.2932 1.4010 0.835 0.8410 0.1489 0.0496
57.2084 29.0 725 57.1899 0.83 0.2953 1.4038 0.83 0.8338 0.1497 0.0511
57.2084 30.0 750 57.1644 0.835 0.2948 1.3923 0.835 0.8374 0.1509 0.0507
57.2084 31.0 775 57.1720 0.83 0.2958 1.4622 0.83 0.8296 0.1502 0.0509
57.2084 32.0 800 57.1365 0.835 0.3024 1.2976 0.835 0.8374 0.1575 0.0509
57.2084 33.0 825 57.1499 0.835 0.2995 1.3654 0.835 0.8308 0.1574 0.0523
57.2084 34.0 850 57.1064 0.83 0.3022 1.3606 0.83 0.8251 0.1578 0.0526
57.2084 35.0 875 57.0901 0.835 0.3003 1.2803 0.835 0.8336 0.1554 0.0516
57.2084 36.0 900 57.0922 0.835 0.3047 1.2749 0.835 0.8336 0.1571 0.0517
57.2084 37.0 925 57.0673 0.83 0.3034 1.2533 0.83 0.8344 0.1559 0.0509
57.2084 38.0 950 57.0810 0.83 0.3024 1.2718 0.83 0.8344 0.1620 0.0526
57.2084 39.0 975 57.1040 0.835 0.3041 1.2522 0.835 0.8392 0.1571 0.0506
56.1387 40.0 1000 57.0542 0.835 0.3024 1.3210 0.835 0.8392 0.1525 0.0501
56.1387 41.0 1025 57.0554 0.83 0.3037 1.3231 0.83 0.8344 0.1534 0.0508
56.1387 42.0 1050 57.0724 0.83 0.2989 1.2517 0.83 0.8344 0.1485 0.0495
56.1387 43.0 1075 57.0429 0.835 0.3010 1.3082 0.835 0.8401 0.1557 0.0506
56.1387 44.0 1100 57.0208 0.835 0.3001 1.2428 0.835 0.8392 0.1583 0.0496
56.1387 45.0 1125 57.0700 0.835 0.2996 1.3149 0.835 0.8454 0.1601 0.0509
56.1387 46.0 1150 57.0054 0.835 0.2950 1.3019 0.835 0.8407 0.1476 0.0492
56.1387 47.0 1175 57.0516 0.825 0.3000 1.2344 0.825 0.8317 0.1485 0.0511
56.1387 48.0 1200 57.0373 0.835 0.3008 1.3016 0.835 0.8434 0.1611 0.0498
56.1387 49.0 1225 57.0154 0.83 0.2982 1.2376 0.83 0.8329 0.1515 0.0501
56.1387 50.0 1250 57.0000 0.835 0.2982 1.2196 0.835 0.8434 0.1535 0.0493
56.1387 51.0 1275 57.0054 0.825 0.2987 1.2217 0.825 0.8352 0.1517 0.0505
56.1387 52.0 1300 57.0347 0.835 0.2996 1.2239 0.835 0.8407 0.1643 0.0486
56.1387 53.0 1325 57.0183 0.835 0.2989 1.2208 0.835 0.8411 0.1604 0.0495
56.1387 54.0 1350 57.0094 0.845 0.2925 1.1545 0.845 0.8494 0.1515 0.0486
56.1387 55.0 1375 57.0027 0.83 0.2974 1.2161 0.83 0.8380 0.1538 0.0491
56.1387 56.0 1400 57.0060 0.835 0.2975 1.2215 0.835 0.8407 0.1546 0.0505
56.1387 57.0 1425 56.9898 0.835 0.2959 1.1432 0.835 0.8411 0.1483 0.0501
56.1387 58.0 1450 56.9907 0.835 0.2963 1.1437 0.835 0.8406 0.1527 0.0485
56.1387 59.0 1475 56.9578 0.84 0.2935 1.1583 0.8400 0.8439 0.1513 0.0488
55.9877 60.0 1500 57.0032 0.84 0.2957 1.2160 0.8400 0.8439 0.1460 0.0502
55.9877 61.0 1525 56.9880 0.835 0.2990 1.2836 0.835 0.8406 0.1475 0.0489
55.9877 62.0 1550 56.9920 0.83 0.2973 1.2071 0.83 0.8349 0.1519 0.0494
55.9877 63.0 1575 56.9681 0.835 0.2978 1.2076 0.835 0.8406 0.1465 0.0483
55.9877 64.0 1600 56.9772 0.835 0.3003 1.1997 0.835 0.8406 0.1567 0.0489
55.9877 65.0 1625 56.9705 0.835 0.2973 1.2038 0.835 0.8406 0.1520 0.0495
55.9877 66.0 1650 56.9682 0.835 0.2977 1.2005 0.835 0.8406 0.1576 0.0488
55.9877 67.0 1675 56.9775 0.835 0.2981 1.2093 0.835 0.8406 0.1497 0.0501
55.9877 68.0 1700 56.9762 0.835 0.2989 1.2061 0.835 0.8406 0.1626 0.0491
55.9877 69.0 1725 56.9807 0.84 0.2978 1.2023 0.8400 0.8434 0.1503 0.0481
55.9877 70.0 1750 56.9705 0.835 0.2988 1.1987 0.835 0.8406 0.1564 0.0487
55.9877 71.0 1775 56.9752 0.83 0.2987 1.2027 0.83 0.8349 0.1593 0.0497
55.9877 72.0 1800 56.9957 0.83 0.2996 1.2060 0.83 0.8349 0.1607 0.0496
55.9877 73.0 1825 56.9697 0.84 0.2966 1.1977 0.8400 0.8434 0.1510 0.0487
55.9877 74.0 1850 56.9644 0.83 0.2997 1.2055 0.83 0.8349 0.1528 0.0506
55.9877 75.0 1875 56.9677 0.84 0.2968 1.1969 0.8400 0.8434 0.1536 0.0495
55.9877 76.0 1900 56.9609 0.84 0.2958 1.1921 0.8400 0.8434 0.1531 0.0495
55.9877 77.0 1925 56.9663 0.835 0.2965 1.1950 0.835 0.8406 0.1576 0.0494
55.9877 78.0 1950 56.9796 0.83 0.2968 1.2049 0.83 0.8349 0.1525 0.0496
55.9877 79.0 1975 56.9648 0.835 0.2966 1.1944 0.835 0.8406 0.1545 0.0494
55.9237 80.0 2000 56.9596 0.845 0.2944 1.1912 0.845 0.8480 0.1543 0.0492
55.9237 81.0 2025 56.9596 0.84 0.2951 1.1878 0.8400 0.8434 0.1546 0.0492
55.9237 82.0 2050 56.9737 0.84 0.2958 1.1954 0.8400 0.8434 0.1521 0.0498
55.9237 83.0 2075 56.9725 0.835 0.2974 1.1963 0.835 0.8377 0.1512 0.0500
55.9237 84.0 2100 56.9743 0.835 0.2978 1.1928 0.835 0.8406 0.1554 0.0500
55.9237 85.0 2125 56.9788 0.835 0.2971 1.1952 0.835 0.8377 0.1493 0.0500
55.9237 86.0 2150 56.9705 0.84 0.2968 1.1933 0.8400 0.8434 0.1541 0.0499
55.9237 87.0 2175 56.9684 0.835 0.2966 1.1926 0.835 0.8377 0.1517 0.0497
55.9237 88.0 2200 56.9725 0.835 0.2979 1.1934 0.835 0.8377 0.1548 0.0497
55.9237 89.0 2225 56.9704 0.84 0.2959 1.1934 0.8400 0.8434 0.1527 0.0495
55.9237 90.0 2250 56.9681 0.84 0.2950 1.1907 0.8400 0.8434 0.1503 0.0498
55.9237 91.0 2275 56.9763 0.835 0.2979 1.1934 0.835 0.8377 0.1516 0.0501
55.9237 92.0 2300 56.9649 0.835 0.2959 1.1889 0.835 0.8377 0.1501 0.0495
55.9237 93.0 2325 56.9687 0.835 0.2959 1.1871 0.835 0.8377 0.1519 0.0501
55.9237 94.0 2350 56.9663 0.835 0.2963 1.1901 0.835 0.8377 0.1533 0.0496
55.9237 95.0 2375 56.9674 0.84 0.2955 1.1895 0.8400 0.8434 0.1534 0.0498
55.9237 96.0 2400 56.9661 0.835 0.2966 1.1907 0.835 0.8377 0.1520 0.0496
55.9237 97.0 2425 56.9623 0.84 0.2958 1.1871 0.8400 0.8434 0.1532 0.0499
55.9237 98.0 2450 56.9694 0.835 0.2969 1.1897 0.835 0.8377 0.1543 0.0499
55.9237 99.0 2475 56.9698 0.835 0.2967 1.1906 0.835 0.8377 0.1543 0.0499
55.8955 100.0 2500 56.9670 0.835 0.2969 1.1900 0.835 0.8377 0.1545 0.0499

Framework versions