generated_from_trainer

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6_e_200-tiny_tobacco3482

This model is a fine-tuned version of WinKawaks/vit-tiny-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 0.6199 0.545 0.5837 2.2367 0.545 0.4488 0.2385 0.2462
No log 2.0 50 0.4278 0.72 0.4443 1.6749 0.72 0.7298 0.3095 0.1339
No log 3.0 75 0.6756 0.625 0.4913 2.4923 0.625 0.5751 0.2278 0.1729
No log 4.0 100 0.6851 0.615 0.5031 2.5374 0.615 0.5988 0.2487 0.1568
No log 5.0 125 0.5550 0.69 0.4473 1.6315 0.69 0.6549 0.2726 0.1697
No log 6.0 150 0.4135 0.79 0.3326 1.3743 0.79 0.7851 0.2019 0.0767
No log 7.0 175 0.4111 0.77 0.3527 1.6472 0.7700 0.7388 0.1917 0.0849
No log 8.0 200 0.4809 0.745 0.3805 2.1093 0.745 0.7260 0.2375 0.0818
No log 9.0 225 0.6527 0.65 0.4651 2.5269 0.65 0.6271 0.2237 0.1333
No log 10.0 250 0.5215 0.715 0.4203 1.7818 0.715 0.6875 0.2155 0.1328
No log 11.0 275 0.5673 0.64 0.4965 2.1840 0.64 0.5458 0.2547 0.1750
No log 12.0 300 0.4713 0.75 0.3879 2.0629 0.75 0.7397 0.2143 0.1262
No log 13.0 325 0.5793 0.655 0.4791 2.6089 0.655 0.6206 0.2461 0.1870
No log 14.0 350 0.6098 0.685 0.4375 2.0773 0.685 0.6802 0.2415 0.1480
No log 15.0 375 0.5338 0.65 0.4777 2.1062 0.65 0.6267 0.2486 0.1577
No log 16.0 400 0.6278 0.675 0.4482 2.3275 0.675 0.6822 0.2425 0.1606
No log 17.0 425 0.5165 0.69 0.4524 2.1670 0.69 0.6661 0.2650 0.1554
No log 18.0 450 0.6064 0.64 0.4978 2.5380 0.64 0.5838 0.2508 0.1850
No log 19.0 475 0.6753 0.645 0.5125 2.4190 0.645 0.5875 0.2664 0.2124
0.3785 20.0 500 0.6946 0.65 0.5331 3.1366 0.65 0.6336 0.2715 0.2605
0.3785 21.0 525 0.5328 0.695 0.4699 2.8365 0.695 0.6863 0.2500 0.1660
0.3785 22.0 550 0.6684 0.62 0.5374 3.2087 0.62 0.6071 0.2363 0.2429
0.3785 23.0 575 0.7235 0.615 0.5613 3.4750 0.615 0.5866 0.2748 0.2185
0.3785 24.0 600 0.6748 0.67 0.5028 3.0615 0.67 0.6185 0.2697 0.2251
0.3785 25.0 625 0.6778 0.645 0.5068 2.7608 0.645 0.6235 0.2442 0.1589
0.3785 26.0 650 0.7163 0.6 0.5690 2.7443 0.6 0.5766 0.2655 0.2821
0.3785 27.0 675 0.7571 0.635 0.5278 3.3670 0.635 0.6085 0.2635 0.2025
0.3785 28.0 700 0.6955 0.605 0.5718 3.1717 0.605 0.5973 0.3092 0.2624
0.3785 29.0 725 0.7951 0.585 0.5869 3.2346 0.585 0.5777 0.2849 0.3039
0.3785 30.0 750 0.5426 0.655 0.4898 2.6384 0.655 0.6295 0.2758 0.1781
0.3785 31.0 775 0.7721 0.6 0.5956 3.5480 0.6 0.5717 0.2908 0.2548
0.3785 32.0 800 0.6102 0.65 0.4974 2.6613 0.65 0.6348 0.2529 0.1661
0.3785 33.0 825 0.7592 0.62 0.5666 3.5174 0.62 0.5736 0.2821 0.2752
0.3785 34.0 850 0.6516 0.655 0.5283 3.1254 0.655 0.6341 0.2596 0.1954
0.3785 35.0 875 0.6626 0.65 0.5329 2.9794 0.65 0.6120 0.2793 0.2390
0.3785 36.0 900 0.6939 0.66 0.5190 3.4020 0.66 0.6258 0.2473 0.1785
0.3785 37.0 925 0.7580 0.605 0.5970 3.1545 0.605 0.5466 0.2996 0.2424
0.3785 38.0 950 0.6088 0.655 0.5187 2.7205 0.655 0.6457 0.2636 0.2413
0.3785 39.0 975 0.7394 0.605 0.5815 2.8167 0.605 0.5798 0.2975 0.2782
0.0886 40.0 1000 0.6910 0.65 0.5015 2.9680 0.65 0.5993 0.2697 0.1652
0.0886 41.0 1025 0.6618 0.635 0.5752 3.5088 0.635 0.5937 0.2929 0.2653
0.0886 42.0 1050 0.7742 0.6 0.5556 3.5946 0.6 0.5644 0.2556 0.1974
0.0886 43.0 1075 0.7379 0.62 0.5589 2.7882 0.62 0.6042 0.3169 0.2143
0.0886 44.0 1100 0.6702 0.64 0.5359 2.9335 0.64 0.6088 0.2765 0.2133
0.0886 45.0 1125 0.8900 0.585 0.6173 3.8349 0.585 0.5639 0.2934 0.2364
0.0886 46.0 1150 0.7800 0.62 0.5707 3.2446 0.62 0.6171 0.3002 0.2156
0.0886 47.0 1175 0.8554 0.57 0.6256 3.6828 0.57 0.5583 0.3191 0.2611
0.0886 48.0 1200 0.6486 0.67 0.4911 3.4792 0.67 0.6449 0.2741 0.1870
0.0886 49.0 1225 0.7315 0.59 0.5829 3.4916 0.59 0.5963 0.2720 0.2101
0.0886 50.0 1250 0.6939 0.665 0.5022 2.9091 0.665 0.6362 0.2743 0.1829
0.0886 51.0 1275 0.7256 0.625 0.5687 3.4914 0.625 0.5740 0.2943 0.2493
0.0886 52.0 1300 0.6374 0.66 0.5144 2.7071 0.66 0.6297 0.2529 0.2006
0.0886 53.0 1325 0.7862 0.645 0.5470 3.2902 0.645 0.6385 0.2899 0.2053
0.0886 54.0 1350 0.7717 0.63 0.5762 3.8614 0.63 0.6027 0.2954 0.2150
0.0886 55.0 1375 0.6664 0.675 0.5120 3.1014 0.675 0.6582 0.2850 0.1842
0.0886 56.0 1400 0.6957 0.615 0.5602 3.0253 0.615 0.5977 0.3033 0.2229
0.0886 57.0 1425 0.6794 0.64 0.5581 3.0174 0.64 0.6205 0.2802 0.2056
0.0886 58.0 1450 0.6345 0.655 0.5162 2.7909 0.655 0.6422 0.2856 0.2789
0.0886 59.0 1475 0.6447 0.655 0.5271 2.9860 0.655 0.6432 0.2735 0.1774
0.0219 60.0 1500 0.7042 0.665 0.5404 3.1132 0.665 0.6268 0.2871 0.2981
0.0219 61.0 1525 0.7288 0.64 0.5486 3.3084 0.64 0.6225 0.2869 0.1861
0.0219 62.0 1550 0.6605 0.69 0.5078 2.9123 0.69 0.6642 0.2668 0.2487
0.0219 63.0 1575 0.5905 0.715 0.4712 3.4707 0.715 0.7013 0.2548 0.2257
0.0219 64.0 1600 0.6209 0.69 0.4940 2.6873 0.69 0.6770 0.2771 0.2263
0.0219 65.0 1625 0.6039 0.68 0.4914 2.6448 0.68 0.6620 0.2926 0.2184
0.0219 66.0 1650 0.5985 0.69 0.4918 2.7592 0.69 0.6757 0.2844 0.2181
0.0219 67.0 1675 0.5955 0.69 0.4903 2.7566 0.69 0.6757 0.2617 0.2227
0.0219 68.0 1700 0.5944 0.69 0.4898 2.7730 0.69 0.6757 0.2683 0.2211
0.0219 69.0 1725 0.5934 0.695 0.4893 2.7575 0.695 0.6823 0.2666 0.2171
0.0219 70.0 1750 0.5913 0.695 0.4890 2.7043 0.695 0.6823 0.2649 0.2160
0.0219 71.0 1775 0.5904 0.69 0.4888 2.7476 0.69 0.6742 0.2718 0.2163
0.0219 72.0 1800 0.5895 0.69 0.4883 2.7463 0.69 0.6742 0.2714 0.2160
0.0219 73.0 1825 0.5882 0.69 0.4877 2.7478 0.69 0.6742 0.2779 0.2171
0.0219 74.0 1850 0.5878 0.69 0.4876 2.7489 0.69 0.6742 0.2813 0.2169
0.0219 75.0 1875 0.5879 0.69 0.4871 2.7592 0.69 0.6742 0.2765 0.2185
0.0219 76.0 1900 0.5868 0.69 0.4870 2.8058 0.69 0.6742 0.2670 0.2183
0.0219 77.0 1925 0.5843 0.69 0.4864 2.8037 0.69 0.6745 0.2764 0.2185
0.0219 78.0 1950 0.5844 0.69 0.4862 2.8040 0.69 0.6745 0.2788 0.2191
0.0219 79.0 1975 0.5831 0.69 0.4857 2.8018 0.69 0.6745 0.2655 0.2178
0.0013 80.0 2000 0.5846 0.69 0.4858 2.8022 0.69 0.6745 0.2633 0.2182
0.0013 81.0 2025 0.5821 0.69 0.4851 2.8020 0.69 0.6745 0.2750 0.2177
0.0013 82.0 2050 0.5826 0.685 0.4852 2.8013 0.685 0.6713 0.2728 0.2180
0.0013 83.0 2075 0.5821 0.685 0.4851 2.8005 0.685 0.6713 0.2705 0.2179
0.0013 84.0 2100 0.5817 0.685 0.4850 2.8007 0.685 0.6713 0.2773 0.2180
0.0013 85.0 2125 0.5814 0.685 0.4849 2.7998 0.685 0.6713 0.2740 0.2176
0.0013 86.0 2150 0.5814 0.685 0.4848 2.7997 0.685 0.6713 0.2686 0.2174
0.0013 87.0 2175 0.5807 0.68 0.4847 2.7994 0.68 0.6624 0.2658 0.2186
0.0013 88.0 2200 0.5803 0.68 0.4845 2.7992 0.68 0.6624 0.2703 0.2180
0.0013 89.0 2225 0.5805 0.68 0.4846 2.7990 0.68 0.6624 0.2632 0.2194
0.0013 90.0 2250 0.5803 0.685 0.4846 2.7979 0.685 0.6703 0.2596 0.2183
0.0013 91.0 2275 0.5805 0.685 0.4847 2.7980 0.685 0.6703 0.2674 0.2183
0.0013 92.0 2300 0.5805 0.685 0.4846 2.7993 0.685 0.6703 0.2562 0.2181
0.0013 93.0 2325 0.5802 0.68 0.4847 2.7974 0.68 0.6624 0.2598 0.2182
0.0013 94.0 2350 0.5800 0.68 0.4846 2.7981 0.68 0.6624 0.2613 0.2175
0.0013 95.0 2375 0.5796 0.68 0.4846 2.7985 0.68 0.6624 0.2589 0.2179
0.0013 96.0 2400 0.5799 0.68 0.4846 2.7980 0.68 0.6624 0.2560 0.2183
0.0013 97.0 2425 0.5796 0.68 0.4846 2.7978 0.68 0.6624 0.2588 0.2175
0.0013 98.0 2450 0.5798 0.68 0.4846 2.7977 0.68 0.6624 0.2589 0.2179
0.0013 99.0 2475 0.5797 0.68 0.4846 2.7977 0.68 0.6624 0.2589 0.2178
0.0003 100.0 2500 0.5797 0.68 0.4846 2.7977 0.68 0.6624 0.2589 0.2179

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