generated_from_trainer

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60-tiny_tobacco3482_hint_

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 66.6267 0.26 0.8706 4.9000 0.26 0.1920 0.2904 0.7812
No log 2.0 50 65.8408 0.54 0.5951 2.8543 0.54 0.4535 0.2542 0.2567
No log 3.0 75 65.3708 0.675 0.4400 1.6094 0.675 0.6134 0.2395 0.1333
No log 4.0 100 65.0889 0.76 0.3809 1.5505 0.76 0.7422 0.2333 0.1125
No log 5.0 125 64.7800 0.8 0.3080 1.7523 0.8000 0.7663 0.1734 0.0708
No log 6.0 150 64.6296 0.78 0.3286 1.7771 0.78 0.7427 0.1752 0.0642
No log 7.0 175 64.3879 0.765 0.3584 1.7400 0.765 0.6986 0.1799 0.0937
No log 8.0 200 64.4361 0.72 0.4640 1.4368 0.72 0.7385 0.2350 0.1314
No log 9.0 225 64.2223 0.76 0.3846 1.6420 0.76 0.7417 0.2006 0.0915
No log 10.0 250 64.2618 0.725 0.4268 1.6667 0.7250 0.7132 0.2131 0.1110
No log 11.0 275 64.2839 0.7 0.4830 1.7975 0.7 0.6829 0.2213 0.1207
No log 12.0 300 64.0218 0.785 0.3523 1.7098 0.785 0.7363 0.1742 0.0702
No log 13.0 325 63.8071 0.78 0.3218 1.4587 0.78 0.7574 0.1640 0.0674
No log 14.0 350 64.7387 0.645 0.5871 2.0188 0.645 0.6360 0.2996 0.1765
No log 15.0 375 64.2173 0.765 0.3832 1.8093 0.765 0.6909 0.1978 0.0892
No log 16.0 400 64.2233 0.765 0.3897 1.4456 0.765 0.7432 0.1983 0.0805
No log 17.0 425 63.7977 0.825 0.2971 1.4248 0.825 0.8057 0.1583 0.0546
No log 18.0 450 63.5818 0.82 0.2983 1.3079 0.82 0.7936 0.1532 0.0474
No log 19.0 475 64.1935 0.78 0.3764 1.6662 0.78 0.7618 0.1911 0.0669
63.0313 20.0 500 63.6054 0.825 0.2871 1.4054 0.825 0.8118 0.1605 0.0520
63.0313 21.0 525 63.6316 0.79 0.3258 1.3131 0.79 0.7714 0.1632 0.0485
63.0313 22.0 550 63.6978 0.84 0.2935 1.2425 0.8400 0.8236 0.1508 0.0586
63.0313 23.0 575 63.8266 0.825 0.3117 1.5766 0.825 0.8019 0.1550 0.0554
63.0313 24.0 600 63.6750 0.825 0.3130 1.1848 0.825 0.8158 0.1553 0.0462
63.0313 25.0 625 63.8469 0.82 0.3259 1.3997 0.82 0.8007 0.1603 0.0564
63.0313 26.0 650 63.7656 0.815 0.3285 1.2752 0.815 0.7969 0.1656 0.0535
63.0313 27.0 675 63.8074 0.805 0.3455 1.1282 0.805 0.7870 0.1732 0.0542
63.0313 28.0 700 63.8411 0.81 0.3437 1.1501 0.81 0.7917 0.1759 0.0529
63.0313 29.0 725 63.8158 0.81 0.3345 1.1519 0.81 0.7901 0.1706 0.0544
63.0313 30.0 750 63.7917 0.815 0.3383 1.2013 0.815 0.8006 0.1706 0.0557
63.0313 31.0 775 63.7855 0.815 0.3396 1.2088 0.815 0.7974 0.1687 0.0551
63.0313 32.0 800 63.8003 0.825 0.3297 1.2233 0.825 0.8091 0.1694 0.0547
63.0313 33.0 825 63.8029 0.815 0.3405 1.2628 0.815 0.8007 0.1729 0.0547
63.0313 34.0 850 63.7752 0.81 0.3352 1.2587 0.81 0.7979 0.1727 0.0574
63.0313 35.0 875 63.7800 0.815 0.3346 1.1948 0.815 0.7977 0.1679 0.0560
63.0313 36.0 900 63.7885 0.825 0.3313 1.2728 0.825 0.8173 0.1591 0.0569
63.0313 37.0 925 63.7730 0.815 0.3354 1.2726 0.815 0.8027 0.1689 0.0555
63.0313 38.0 950 63.8327 0.815 0.3405 1.4350 0.815 0.8043 0.1675 0.0632
63.0313 39.0 975 63.7324 0.785 0.3686 1.6439 0.785 0.7745 0.1808 0.0666
61.6786 40.0 1000 63.8625 0.765 0.3946 1.6127 0.765 0.7727 0.1961 0.0723
61.6786 41.0 1025 64.1254 0.765 0.3904 1.5456 0.765 0.7570 0.2020 0.0850
61.6786 42.0 1050 63.6201 0.78 0.3728 1.4198 0.78 0.7447 0.1869 0.0647
61.6786 43.0 1075 63.6033 0.835 0.2968 1.5430 0.835 0.8059 0.1574 0.0479
61.6786 44.0 1100 63.6777 0.795 0.3606 1.3542 0.795 0.7638 0.1806 0.0529
61.6786 45.0 1125 63.5747 0.83 0.2996 1.5403 0.83 0.8079 0.1450 0.0504
61.6786 46.0 1150 63.6022 0.805 0.3389 1.3842 0.805 0.7791 0.1794 0.0466
61.6786 47.0 1175 63.6342 0.81 0.3346 1.2861 0.81 0.7811 0.1678 0.0476
61.6786 48.0 1200 63.6065 0.81 0.3298 1.2911 0.81 0.7807 0.1654 0.0465
61.6786 49.0 1225 63.5937 0.815 0.3260 1.3576 0.815 0.7844 0.1613 0.0467
61.6786 50.0 1250 63.6029 0.815 0.3241 1.2826 0.815 0.7844 0.1662 0.0467
61.6786 51.0 1275 63.5947 0.81 0.3232 1.4156 0.81 0.7789 0.1631 0.0471
61.6786 52.0 1300 63.6501 0.81 0.3268 1.4148 0.81 0.7785 0.1703 0.0468
61.6786 53.0 1325 63.6207 0.81 0.3207 1.2785 0.81 0.7785 0.1698 0.0479
61.6786 54.0 1350 63.6021 0.815 0.3233 1.3519 0.815 0.7818 0.1629 0.0456
61.6786 55.0 1375 63.6128 0.815 0.3207 1.2837 0.815 0.7818 0.1641 0.0474
61.6786 56.0 1400 63.5974 0.81 0.3194 1.3542 0.81 0.7789 0.1679 0.0474
61.6786 57.0 1425 63.6173 0.81 0.3260 1.2907 0.81 0.7761 0.1653 0.0486
61.6786 58.0 1450 63.6057 0.81 0.3163 1.2981 0.81 0.7789 0.1651 0.0471
61.6786 59.0 1475 63.6052 0.81 0.3197 1.3444 0.81 0.7789 0.1680 0.0467
61.52 60.0 1500 63.5865 0.82 0.3143 1.2748 0.82 0.7920 0.1617 0.0465
61.52 61.0 1525 63.5754 0.82 0.3126 1.2677 0.82 0.7920 0.1595 0.0468
61.52 62.0 1550 63.5876 0.815 0.3120 1.2691 0.815 0.7879 0.1567 0.0478
61.52 63.0 1575 63.6040 0.82 0.3110 1.2632 0.82 0.7920 0.1526 0.0472
61.52 64.0 1600 63.5956 0.82 0.3111 1.1976 0.82 0.7963 0.1592 0.0468
61.52 65.0 1625 63.5792 0.815 0.3095 1.1928 0.815 0.7879 0.1571 0.0469
61.52 66.0 1650 63.5704 0.82 0.3086 1.2509 0.82 0.7936 0.1543 0.0467
61.52 67.0 1675 63.5918 0.82 0.3118 1.2536 0.82 0.7936 0.1619 0.0471
61.52 68.0 1700 63.5741 0.82 0.3072 1.2491 0.82 0.7963 0.1562 0.0465
61.52 69.0 1725 63.5581 0.825 0.3085 1.2490 0.825 0.8021 0.1566 0.0460
61.52 70.0 1750 63.5796 0.82 0.3087 1.2456 0.82 0.7963 0.1556 0.0471
61.52 71.0 1775 63.5776 0.825 0.3073 1.2530 0.825 0.8021 0.1571 0.0474
61.52 72.0 1800 63.5524 0.825 0.3064 1.2402 0.825 0.8021 0.1555 0.0465
61.52 73.0 1825 63.5638 0.825 0.3075 1.2465 0.825 0.8021 0.1607 0.0466
61.52 74.0 1850 63.5654 0.82 0.3058 1.2425 0.82 0.7963 0.1552 0.0468
61.52 75.0 1875 63.5654 0.825 0.3041 1.2439 0.825 0.8021 0.1563 0.0466
61.52 76.0 1900 63.5499 0.83 0.3018 1.2432 0.83 0.8082 0.1541 0.0463
61.52 77.0 1925 63.5563 0.825 0.3059 1.2385 0.825 0.8021 0.1570 0.0466
61.52 78.0 1950 63.5524 0.825 0.3045 1.2364 0.825 0.8021 0.1524 0.0464
61.52 79.0 1975 63.5507 0.825 0.3064 1.2344 0.825 0.8021 0.1523 0.0463
61.4257 80.0 2000 63.5531 0.825 0.3062 1.2266 0.825 0.8035 0.1625 0.0463
61.4257 81.0 2025 63.5486 0.825 0.3029 1.1850 0.825 0.8024 0.1506 0.0463
61.4257 82.0 2050 63.5479 0.82 0.3081 1.2269 0.82 0.7963 0.1588 0.0458
61.4257 83.0 2075 63.5444 0.835 0.3029 1.1721 0.835 0.8139 0.1475 0.0461
61.4257 84.0 2100 63.5435 0.835 0.3047 1.2306 0.835 0.8171 0.1529 0.0464
61.4257 85.0 2125 63.5393 0.83 0.3058 1.2255 0.83 0.8081 0.1462 0.0464
61.4257 86.0 2150 63.5437 0.835 0.3048 1.2254 0.835 0.8171 0.1481 0.0464
61.4257 87.0 2175 63.5463 0.83 0.3039 1.1549 0.83 0.8115 0.1562 0.0463
61.4257 88.0 2200 63.5408 0.835 0.3055 1.2211 0.835 0.8187 0.1485 0.0462
61.4257 89.0 2225 63.5477 0.825 0.3054 1.1541 0.825 0.8024 0.1521 0.0463
61.4257 90.0 2250 63.5383 0.83 0.3051 1.1577 0.83 0.8095 0.1532 0.0463
61.4257 91.0 2275 63.5466 0.84 0.3057 1.1583 0.8400 0.8244 0.1516 0.0458
61.4257 92.0 2300 63.5447 0.835 0.3049 1.1518 0.835 0.8188 0.1615 0.0462
61.4257 93.0 2325 63.5327 0.84 0.3044 1.1540 0.8400 0.8244 0.1508 0.0459
61.4257 94.0 2350 63.5392 0.84 0.3046 1.1506 0.8400 0.8244 0.1569 0.0459
61.4257 95.0 2375 63.5305 0.835 0.3050 1.1520 0.835 0.8188 0.1571 0.0457
61.4257 96.0 2400 63.5413 0.835 0.3042 1.1494 0.835 0.8188 0.1571 0.0461
61.4257 97.0 2425 63.5387 0.835 0.3047 1.1489 0.835 0.8188 0.1652 0.0461
61.4257 98.0 2450 63.5383 0.84 0.3046 1.1503 0.8400 0.8244 0.1568 0.0458
61.4257 99.0 2475 63.5374 0.835 0.3045 1.1489 0.835 0.8188 0.1570 0.0456
61.3919 100.0 2500 63.5396 0.84 0.3043 1.1495 0.8400 0.8244 0.1568 0.0457

Framework versions