generated_from_trainer

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vit-small_rvl_cdip_100_examples_per_class_kd_CEKD_t5.0_a0.9

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 2.8799 0.12 0.9317 15.6566 0.12 0.1217 0.1503 0.8678
No log 2.0 50 2.2166 0.395 0.7576 9.4150 0.395 0.3645 0.2155 0.3726
No log 3.0 75 1.7821 0.505 0.6346 5.5305 0.505 0.4975 0.1755 0.2454
No log 4.0 100 1.6660 0.5275 0.6038 4.9669 0.5275 0.5333 0.1684 0.2324
No log 5.0 125 1.6118 0.54 0.5943 4.8266 0.54 0.5233 0.1947 0.2249
No log 6.0 150 1.7108 0.5275 0.6168 4.4308 0.5275 0.5247 0.2018 0.2418
No log 7.0 175 1.6465 0.5825 0.5721 4.8918 0.5825 0.5614 0.1887 0.1995
No log 8.0 200 1.6441 0.565 0.6040 4.2349 0.565 0.5591 0.1933 0.2216
No log 9.0 225 1.7054 0.565 0.6054 4.6348 0.565 0.5649 0.1845 0.2033
No log 10.0 250 1.6724 0.5375 0.6191 4.3502 0.5375 0.5257 0.1991 0.2223
No log 11.0 275 1.5397 0.57 0.5757 4.1311 0.57 0.5715 0.2079 0.1936
No log 12.0 300 1.7636 0.55 0.6394 5.0515 0.55 0.5376 0.2252 0.2268
No log 13.0 325 1.6080 0.575 0.5997 4.2707 0.575 0.5515 0.2048 0.1887
No log 14.0 350 1.7572 0.575 0.6205 4.6140 0.575 0.5705 0.2203 0.2342
No log 15.0 375 1.5604 0.58 0.5872 3.8633 0.58 0.5762 0.2089 0.1866
No log 16.0 400 1.6440 0.585 0.6042 4.2508 0.585 0.5940 0.2253 0.2182
No log 17.0 425 1.6117 0.5825 0.6057 4.2511 0.5825 0.5732 0.2299 0.1947
No log 18.0 450 1.5597 0.605 0.5732 4.4755 0.605 0.6028 0.2101 0.1721
No log 19.0 475 1.4177 0.6325 0.5429 3.4771 0.6325 0.6319 0.1930 0.1786
0.5354 20.0 500 1.5745 0.56 0.6076 3.6058 0.56 0.5643 0.2265 0.1898
0.5354 21.0 525 1.4907 0.6125 0.5682 3.9837 0.6125 0.6184 0.1981 0.1810
0.5354 22.0 550 1.4494 0.5925 0.5677 3.2864 0.5925 0.5906 0.2187 0.1670
0.5354 23.0 575 1.5608 0.62 0.5830 4.0132 0.62 0.6029 0.2286 0.1808
0.5354 24.0 600 1.5038 0.58 0.5957 3.6519 0.58 0.5956 0.2321 0.1879
0.5354 25.0 625 1.4094 0.615 0.5554 3.0313 0.615 0.6102 0.2180 0.1689
0.5354 26.0 650 1.4485 0.62 0.5712 3.3326 0.62 0.6181 0.2138 0.1729
0.5354 27.0 675 1.4156 0.6225 0.5621 3.2257 0.6225 0.6239 0.2158 0.1718
0.5354 28.0 700 1.3729 0.6275 0.5476 3.1300 0.6275 0.6285 0.2078 0.1620
0.5354 29.0 725 1.3671 0.6275 0.5337 3.4625 0.6275 0.6285 0.2177 0.1586
0.5354 30.0 750 1.3263 0.63 0.5380 3.2177 0.63 0.6338 0.2063 0.1577
0.5354 31.0 775 1.2991 0.6225 0.5223 3.0482 0.6225 0.6238 0.1940 0.1525
0.5354 32.0 800 1.3227 0.6325 0.5333 2.9622 0.6325 0.6351 0.1906 0.1554
0.5354 33.0 825 1.3077 0.63 0.5298 3.2060 0.63 0.6338 0.1933 0.1555
0.5354 34.0 850 1.3036 0.6225 0.5269 3.0431 0.6225 0.6242 0.1996 0.1535
0.5354 35.0 875 1.3057 0.6275 0.5263 2.9651 0.6275 0.6291 0.2023 0.1538
0.5354 36.0 900 1.2992 0.6275 0.5247 2.9748 0.6275 0.6289 0.1961 0.1518
0.5354 37.0 925 1.3001 0.6325 0.5252 2.9784 0.6325 0.6347 0.1978 0.1531
0.5354 38.0 950 1.2990 0.63 0.5229 2.9014 0.63 0.6327 0.1981 0.1524
0.5354 39.0 975 1.2995 0.6325 0.5246 2.9776 0.6325 0.6354 0.1946 0.1533
0.0336 40.0 1000 1.2945 0.6275 0.5226 2.9029 0.6275 0.6302 0.1965 0.1523
0.0336 41.0 1025 1.3023 0.63 0.5247 3.0515 0.63 0.6341 0.2044 0.1534
0.0336 42.0 1050 1.2990 0.635 0.5239 3.0673 0.635 0.6381 0.1952 0.1516
0.0336 43.0 1075 1.2962 0.635 0.5213 3.0585 0.635 0.6378 0.2055 0.1523
0.0336 44.0 1100 1.2991 0.625 0.5229 2.9801 0.625 0.6278 0.1954 0.1532
0.0336 45.0 1125 1.2949 0.6375 0.5222 3.0564 0.6375 0.6419 0.2027 0.1519
0.0336 46.0 1150 1.2989 0.6275 0.5228 3.0737 0.6275 0.6308 0.2075 0.1529
0.0336 47.0 1175 1.2902 0.6325 0.5201 3.0606 0.6325 0.6360 0.2099 0.1516
0.0336 48.0 1200 1.2971 0.6275 0.5217 3.0829 0.6275 0.6305 0.1882 0.1518
0.0336 49.0 1225 1.2913 0.63 0.5212 2.9853 0.63 0.6332 0.1928 0.1524
0.0336 50.0 1250 1.2917 0.63 0.5205 2.9850 0.63 0.6336 0.1910 0.1518
0.0336 51.0 1275 1.2928 0.63 0.5208 3.0579 0.63 0.6330 0.2020 0.1528
0.0336 52.0 1300 1.2941 0.635 0.5205 3.0647 0.635 0.6383 0.1919 0.1515
0.0336 53.0 1325 1.2930 0.635 0.5207 3.0637 0.635 0.6384 0.1868 0.1518
0.0336 54.0 1350 1.2918 0.63 0.5203 3.0628 0.63 0.6335 0.1986 0.1519
0.0336 55.0 1375 1.2894 0.635 0.5198 2.9874 0.635 0.6383 0.2026 0.1514
0.0336 56.0 1400 1.2913 0.63 0.5203 3.0691 0.63 0.6337 0.2045 0.1519
0.0336 57.0 1425 1.2923 0.6325 0.5205 2.9869 0.6325 0.6358 0.1962 0.1522
0.0336 58.0 1450 1.2927 0.6375 0.5199 3.0734 0.6375 0.6408 0.1905 0.1514
0.0336 59.0 1475 1.2931 0.6325 0.5204 3.0607 0.6325 0.6353 0.1980 0.1520
0.0236 60.0 1500 1.2911 0.6325 0.5199 3.0664 0.6325 0.6359 0.1875 0.1517
0.0236 61.0 1525 1.2901 0.635 0.5195 2.9877 0.635 0.6386 0.1907 0.1516
0.0236 62.0 1550 1.2913 0.635 0.5192 3.0655 0.635 0.6383 0.1971 0.1515
0.0236 63.0 1575 1.2920 0.635 0.5201 3.0044 0.635 0.6379 0.1991 0.1514
0.0236 64.0 1600 1.2911 0.635 0.5192 3.0654 0.635 0.6380 0.1848 0.1509
0.0236 65.0 1625 1.2924 0.635 0.5196 3.1438 0.635 0.6379 0.1969 0.1515
0.0236 66.0 1650 1.2901 0.635 0.5191 2.9928 0.635 0.6392 0.1978 0.1507
0.0236 67.0 1675 1.2911 0.6325 0.5189 3.0662 0.6325 0.6359 0.1896 0.1517
0.0236 68.0 1700 1.2911 0.6375 0.5193 2.9932 0.6375 0.6404 0.2017 0.1507
0.0236 69.0 1725 1.2893 0.635 0.5189 2.9907 0.635 0.6391 0.1951 0.1511
0.0236 70.0 1750 1.2913 0.6325 0.5195 2.9919 0.6325 0.6362 0.1955 0.1513
0.0236 71.0 1775 1.2899 0.635 0.5188 2.9899 0.635 0.6386 0.2049 0.1511
0.0236 72.0 1800 1.2912 0.635 0.5192 2.9914 0.635 0.6379 0.1924 0.1513
0.0236 73.0 1825 1.2898 0.6325 0.5188 2.9901 0.6325 0.6367 0.2059 0.1511
0.0236 74.0 1850 1.2902 0.635 0.5190 2.9918 0.635 0.6391 0.2069 0.1511
0.0236 75.0 1875 1.2904 0.635 0.5191 2.9916 0.635 0.6391 0.1969 0.1511
0.0236 76.0 1900 1.2905 0.635 0.5191 2.9899 0.635 0.6391 0.1969 0.1512
0.0236 77.0 1925 1.2904 0.635 0.5191 2.9917 0.635 0.6391 0.1926 0.1511
0.0236 78.0 1950 1.2899 0.635 0.5188 2.9909 0.635 0.6391 0.2010 0.1510
0.0236 79.0 1975 1.2900 0.635 0.5188 2.9908 0.635 0.6391 0.2034 0.1511
0.0233 80.0 2000 1.2900 0.635 0.5188 2.9910 0.635 0.6391 0.1967 0.1511
0.0233 81.0 2025 1.2900 0.635 0.5188 2.9911 0.635 0.6391 0.2002 0.1511
0.0233 82.0 2050 1.2901 0.635 0.5189 2.9909 0.635 0.6391 0.1993 0.1511
0.0233 83.0 2075 1.2900 0.635 0.5188 2.9906 0.635 0.6391 0.1937 0.1511
0.0233 84.0 2100 1.2901 0.635 0.5189 2.9917 0.635 0.6391 0.2026 0.1511
0.0233 85.0 2125 1.2899 0.635 0.5188 2.9905 0.635 0.6391 0.1993 0.1512
0.0233 86.0 2150 1.2897 0.635 0.5187 2.9906 0.635 0.6391 0.1976 0.1511
0.0233 87.0 2175 1.2899 0.635 0.5188 2.9905 0.635 0.6391 0.1980 0.1511
0.0233 88.0 2200 1.2897 0.635 0.5187 2.9911 0.635 0.6391 0.1957 0.1511
0.0233 89.0 2225 1.2899 0.635 0.5187 2.9910 0.635 0.6391 0.1970 0.1511
0.0233 90.0 2250 1.2898 0.635 0.5187 2.9905 0.635 0.6391 0.1988 0.1512
0.0233 91.0 2275 1.2897 0.635 0.5187 2.9908 0.635 0.6391 0.1961 0.1511
0.0233 92.0 2300 1.2898 0.635 0.5187 2.9908 0.635 0.6391 0.1966 0.1511
0.0233 93.0 2325 1.2897 0.635 0.5186 2.9908 0.635 0.6391 0.1984 0.1511
0.0233 94.0 2350 1.2898 0.635 0.5187 2.9907 0.635 0.6391 0.2009 0.1511
0.0233 95.0 2375 1.2897 0.635 0.5186 2.9908 0.635 0.6391 0.2023 0.1511
0.0233 96.0 2400 1.2897 0.635 0.5186 2.9908 0.635 0.6391 0.1985 0.1511
0.0233 97.0 2425 1.2897 0.635 0.5186 2.9908 0.635 0.6391 0.1984 0.1511
0.0233 98.0 2450 1.2897 0.635 0.5186 2.9908 0.635 0.6391 0.1985 0.1511
0.0233 99.0 2475 1.2897 0.635 0.5186 2.9909 0.635 0.6391 0.1984 0.1511
0.0232 100.0 2500 1.2897 0.635 0.5186 2.9908 0.635 0.6391 0.1984 0.1511

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