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vit-tiny_tobacco3482_og_simkd_
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:
- Loss: 212.9255
- Accuracy: 0.825
- Brier Loss: 0.2955
- Nll: 1.3247
- F1 Micro: 0.825
- F1 Macro: 0.8027
- Ece: 0.1660
- Aurc: 0.0554
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:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
---|---|---|---|---|---|---|---|---|---|---|
No log | 1.0 | 25 | 219.5859 | 0.225 | 0.8919 | 5.3905 | 0.225 | 0.1403 | 0.2467 | 0.7026 |
No log | 2.0 | 50 | 218.7605 | 0.385 | 0.8149 | 2.3886 | 0.3850 | 0.3040 | 0.3416 | 0.4009 |
No log | 3.0 | 75 | 217.4839 | 0.49 | 0.6311 | 1.8415 | 0.49 | 0.3775 | 0.2502 | 0.2789 |
No log | 4.0 | 100 | 216.7303 | 0.605 | 0.5512 | 1.9525 | 0.605 | 0.4738 | 0.2423 | 0.1956 |
No log | 5.0 | 125 | 215.7727 | 0.625 | 0.4792 | 1.8491 | 0.625 | 0.5148 | 0.2037 | 0.1503 |
No log | 6.0 | 150 | 215.9141 | 0.595 | 0.5723 | 2.5766 | 0.595 | 0.4836 | 0.2297 | 0.2039 |
No log | 7.0 | 175 | 215.2466 | 0.715 | 0.4245 | 1.8434 | 0.715 | 0.5962 | 0.2236 | 0.1201 |
No log | 8.0 | 200 | 215.0580 | 0.72 | 0.3878 | 1.8760 | 0.72 | 0.6108 | 0.2068 | 0.0879 |
No log | 9.0 | 225 | 214.9401 | 0.745 | 0.3919 | 1.7852 | 0.745 | 0.7183 | 0.1855 | 0.0936 |
No log | 10.0 | 250 | 214.6627 | 0.66 | 0.4840 | 2.1588 | 0.66 | 0.6144 | 0.2371 | 0.1261 |
No log | 11.0 | 275 | 214.9265 | 0.69 | 0.5027 | 1.7910 | 0.69 | 0.6599 | 0.2514 | 0.1279 |
No log | 12.0 | 300 | 214.4700 | 0.78 | 0.3372 | 1.7013 | 0.78 | 0.7459 | 0.1740 | 0.0741 |
No log | 13.0 | 325 | 214.5191 | 0.805 | 0.3164 | 1.5824 | 0.805 | 0.7689 | 0.1662 | 0.0689 |
No log | 14.0 | 350 | 214.3915 | 0.8 | 0.3278 | 1.5290 | 0.8000 | 0.7742 | 0.1716 | 0.0675 |
No log | 15.0 | 375 | 214.2643 | 0.8 | 0.3315 | 1.5964 | 0.8000 | 0.7697 | 0.1491 | 0.0876 |
No log | 16.0 | 400 | 214.2815 | 0.78 | 0.3751 | 1.8388 | 0.78 | 0.7670 | 0.1944 | 0.0836 |
No log | 17.0 | 425 | 214.0954 | 0.78 | 0.3505 | 1.4905 | 0.78 | 0.7521 | 0.1832 | 0.0662 |
No log | 18.0 | 450 | 214.1399 | 0.785 | 0.3392 | 1.2883 | 0.785 | 0.7662 | 0.1760 | 0.0749 |
No log | 19.0 | 475 | 214.1986 | 0.81 | 0.3229 | 1.6305 | 0.81 | 0.7984 | 0.1754 | 0.0777 |
220.3818 | 20.0 | 500 | 214.1931 | 0.815 | 0.2994 | 1.5637 | 0.815 | 0.7940 | 0.1520 | 0.0606 |
220.3818 | 21.0 | 525 | 213.9438 | 0.815 | 0.3066 | 1.4756 | 0.815 | 0.7983 | 0.1616 | 0.0678 |
220.3818 | 22.0 | 550 | 213.9014 | 0.8 | 0.3485 | 1.9629 | 0.8000 | 0.7885 | 0.1838 | 0.0727 |
220.3818 | 23.0 | 575 | 214.0186 | 0.83 | 0.2863 | 1.6314 | 0.83 | 0.8107 | 0.1516 | 0.0574 |
220.3818 | 24.0 | 600 | 213.8764 | 0.805 | 0.3323 | 1.4873 | 0.805 | 0.7903 | 0.1716 | 0.0726 |
220.3818 | 25.0 | 625 | 214.0043 | 0.81 | 0.3094 | 1.5562 | 0.81 | 0.7764 | 0.1625 | 0.0598 |
220.3818 | 26.0 | 650 | 213.6884 | 0.825 | 0.3165 | 1.6150 | 0.825 | 0.8038 | 0.1667 | 0.0755 |
220.3818 | 27.0 | 675 | 213.7763 | 0.81 | 0.3164 | 1.5526 | 0.81 | 0.7904 | 0.1767 | 0.0747 |
220.3818 | 28.0 | 700 | 213.9658 | 0.825 | 0.2996 | 1.7947 | 0.825 | 0.8149 | 0.1686 | 0.0651 |
220.3818 | 29.0 | 725 | 213.7030 | 0.815 | 0.3155 | 1.3772 | 0.815 | 0.8024 | 0.1616 | 0.0613 |
220.3818 | 30.0 | 750 | 213.7211 | 0.805 | 0.3421 | 1.5621 | 0.805 | 0.7986 | 0.1794 | 0.0624 |
220.3818 | 31.0 | 775 | 213.6852 | 0.815 | 0.3094 | 1.5177 | 0.815 | 0.7872 | 0.1500 | 0.0735 |
220.3818 | 32.0 | 800 | 213.6889 | 0.785 | 0.3345 | 1.4134 | 0.785 | 0.7652 | 0.1669 | 0.0563 |
220.3818 | 33.0 | 825 | 213.6302 | 0.805 | 0.3298 | 1.8630 | 0.805 | 0.7865 | 0.1689 | 0.0693 |
220.3818 | 34.0 | 850 | 213.6116 | 0.83 | 0.2890 | 1.5365 | 0.83 | 0.8033 | 0.1555 | 0.0661 |
220.3818 | 35.0 | 875 | 213.6136 | 0.805 | 0.3026 | 1.1797 | 0.805 | 0.7744 | 0.1551 | 0.0477 |
220.3818 | 36.0 | 900 | 213.5340 | 0.815 | 0.3008 | 1.6963 | 0.815 | 0.7938 | 0.1531 | 0.0687 |
220.3818 | 37.0 | 925 | 213.5380 | 0.84 | 0.2968 | 1.3848 | 0.8400 | 0.8396 | 0.1631 | 0.0577 |
220.3818 | 38.0 | 950 | 213.5322 | 0.83 | 0.3016 | 1.5511 | 0.83 | 0.8133 | 0.1647 | 0.0599 |
220.3818 | 39.0 | 975 | 213.4971 | 0.82 | 0.3155 | 1.4175 | 0.82 | 0.7999 | 0.1571 | 0.0535 |
217.7955 | 40.0 | 1000 | 213.4139 | 0.825 | 0.3103 | 1.6359 | 0.825 | 0.8043 | 0.1749 | 0.0683 |
217.7955 | 41.0 | 1025 | 213.4513 | 0.83 | 0.3002 | 1.5369 | 0.83 | 0.8139 | 0.1580 | 0.0606 |
217.7955 | 42.0 | 1050 | 213.4196 | 0.8 | 0.3251 | 1.3570 | 0.8000 | 0.7779 | 0.1745 | 0.0608 |
217.7955 | 43.0 | 1075 | 213.3506 | 0.815 | 0.3142 | 1.3579 | 0.815 | 0.7988 | 0.1724 | 0.0563 |
217.7955 | 44.0 | 1100 | 213.3151 | 0.805 | 0.3217 | 1.3796 | 0.805 | 0.7820 | 0.1748 | 0.0580 |
217.7955 | 45.0 | 1125 | 213.3202 | 0.825 | 0.3114 | 1.4198 | 0.825 | 0.8090 | 0.1568 | 0.0614 |
217.7955 | 46.0 | 1150 | 213.3313 | 0.805 | 0.3203 | 1.3750 | 0.805 | 0.7860 | 0.1667 | 0.0563 |
217.7955 | 47.0 | 1175 | 213.3293 | 0.835 | 0.2910 | 1.3909 | 0.835 | 0.8190 | 0.1515 | 0.0576 |
217.7955 | 48.0 | 1200 | 213.2646 | 0.825 | 0.2916 | 1.3674 | 0.825 | 0.8022 | 0.1526 | 0.0577 |
217.7955 | 49.0 | 1225 | 213.2620 | 0.83 | 0.3137 | 1.4579 | 0.83 | 0.8101 | 0.1634 | 0.0565 |
217.7955 | 50.0 | 1250 | 213.2164 | 0.815 | 0.3087 | 1.2599 | 0.815 | 0.7917 | 0.1618 | 0.0573 |
217.7955 | 51.0 | 1275 | 213.2495 | 0.795 | 0.3155 | 1.2060 | 0.795 | 0.7648 | 0.1712 | 0.0573 |
217.7955 | 52.0 | 1300 | 213.2231 | 0.82 | 0.3232 | 1.4463 | 0.82 | 0.8029 | 0.1658 | 0.0544 |
217.7955 | 53.0 | 1325 | 213.2242 | 0.83 | 0.2891 | 1.3586 | 0.83 | 0.8056 | 0.1427 | 0.0520 |
217.7955 | 54.0 | 1350 | 213.2049 | 0.83 | 0.2959 | 1.2968 | 0.83 | 0.8063 | 0.1573 | 0.0523 |
217.7955 | 55.0 | 1375 | 213.1500 | 0.84 | 0.2844 | 1.4084 | 0.8400 | 0.8137 | 0.1490 | 0.0570 |
217.7955 | 56.0 | 1400 | 213.1851 | 0.815 | 0.3097 | 1.4005 | 0.815 | 0.7892 | 0.1605 | 0.0605 |
217.7955 | 57.0 | 1425 | 213.1577 | 0.805 | 0.3130 | 1.2482 | 0.805 | 0.7805 | 0.1635 | 0.0550 |
217.7955 | 58.0 | 1450 | 213.1812 | 0.835 | 0.2943 | 1.3191 | 0.835 | 0.8047 | 0.1584 | 0.0550 |
217.7955 | 59.0 | 1475 | 213.0962 | 0.82 | 0.3102 | 1.3163 | 0.82 | 0.7906 | 0.1672 | 0.0513 |
217.1347 | 60.0 | 1500 | 213.1257 | 0.835 | 0.2876 | 1.3165 | 0.835 | 0.8122 | 0.1433 | 0.0562 |
217.1347 | 61.0 | 1525 | 213.1092 | 0.83 | 0.2896 | 1.3196 | 0.83 | 0.8061 | 0.1533 | 0.0549 |
217.1347 | 62.0 | 1550 | 213.0827 | 0.815 | 0.3072 | 1.3053 | 0.815 | 0.7925 | 0.1546 | 0.0523 |
217.1347 | 63.0 | 1575 | 213.0972 | 0.825 | 0.2965 | 1.2148 | 0.825 | 0.8044 | 0.1472 | 0.0507 |
217.1347 | 64.0 | 1600 | 213.0849 | 0.83 | 0.2923 | 1.3196 | 0.83 | 0.8106 | 0.1637 | 0.0551 |
217.1347 | 65.0 | 1625 | 213.0354 | 0.815 | 0.3158 | 1.2749 | 0.815 | 0.7867 | 0.1675 | 0.0515 |
217.1347 | 66.0 | 1650 | 213.0493 | 0.825 | 0.2993 | 1.3046 | 0.825 | 0.7949 | 0.1636 | 0.0558 |
217.1347 | 67.0 | 1675 | 212.9869 | 0.815 | 0.3081 | 1.3846 | 0.815 | 0.7868 | 0.1579 | 0.0583 |
217.1347 | 68.0 | 1700 | 213.0629 | 0.84 | 0.2915 | 1.3902 | 0.8400 | 0.8046 | 0.1590 | 0.0540 |
217.1347 | 69.0 | 1725 | 213.0391 | 0.825 | 0.3068 | 1.3801 | 0.825 | 0.8015 | 0.1553 | 0.0531 |
217.1347 | 70.0 | 1750 | 212.9991 | 0.835 | 0.2864 | 1.3331 | 0.835 | 0.8097 | 0.1531 | 0.0562 |
217.1347 | 71.0 | 1775 | 213.0157 | 0.83 | 0.2897 | 1.2788 | 0.83 | 0.8002 | 0.1584 | 0.0551 |
217.1347 | 72.0 | 1800 | 212.9134 | 0.82 | 0.3051 | 1.3131 | 0.82 | 0.7960 | 0.1690 | 0.0522 |
217.1347 | 73.0 | 1825 | 213.0014 | 0.825 | 0.2926 | 1.3111 | 0.825 | 0.8040 | 0.1390 | 0.0574 |
217.1347 | 74.0 | 1850 | 212.9525 | 0.82 | 0.2985 | 1.3181 | 0.82 | 0.7962 | 0.1579 | 0.0543 |
217.1347 | 75.0 | 1875 | 212.9581 | 0.815 | 0.3024 | 1.2835 | 0.815 | 0.7810 | 0.1648 | 0.0504 |
217.1347 | 76.0 | 1900 | 213.0073 | 0.835 | 0.2970 | 1.3745 | 0.835 | 0.8095 | 0.1597 | 0.0579 |
217.1347 | 77.0 | 1925 | 213.0066 | 0.805 | 0.3046 | 1.3071 | 0.805 | 0.7783 | 0.1502 | 0.0547 |
217.1347 | 78.0 | 1950 | 212.9872 | 0.82 | 0.3018 | 1.4088 | 0.82 | 0.7928 | 0.1527 | 0.0527 |
217.1347 | 79.0 | 1975 | 212.9629 | 0.82 | 0.3024 | 1.3665 | 0.82 | 0.8012 | 0.1626 | 0.0551 |
216.794 | 80.0 | 2000 | 212.9545 | 0.825 | 0.3080 | 1.3609 | 0.825 | 0.8062 | 0.1652 | 0.0541 |
216.794 | 81.0 | 2025 | 212.9253 | 0.825 | 0.3077 | 1.3779 | 0.825 | 0.8044 | 0.1662 | 0.0547 |
216.794 | 82.0 | 2050 | 212.9501 | 0.82 | 0.3024 | 1.3636 | 0.82 | 0.7928 | 0.1677 | 0.0553 |
216.794 | 83.0 | 2075 | 212.9160 | 0.81 | 0.3055 | 1.3686 | 0.81 | 0.7786 | 0.1624 | 0.0578 |
216.794 | 84.0 | 2100 | 212.9532 | 0.84 | 0.2914 | 1.4589 | 0.8400 | 0.8129 | 0.1482 | 0.0510 |
216.794 | 85.0 | 2125 | 212.9397 | 0.825 | 0.3067 | 1.3768 | 0.825 | 0.7981 | 0.1653 | 0.0537 |
216.794 | 86.0 | 2150 | 212.8927 | 0.83 | 0.2980 | 1.3825 | 0.83 | 0.8118 | 0.1662 | 0.0560 |
216.794 | 87.0 | 2175 | 212.8856 | 0.825 | 0.3004 | 1.4017 | 0.825 | 0.8063 | 0.1595 | 0.0555 |
216.794 | 88.0 | 2200 | 212.9423 | 0.82 | 0.3033 | 1.3619 | 0.82 | 0.8012 | 0.1539 | 0.0517 |
216.794 | 89.0 | 2225 | 212.8776 | 0.84 | 0.2922 | 1.3845 | 0.8400 | 0.8176 | 0.1555 | 0.0537 |
216.794 | 90.0 | 2250 | 212.9439 | 0.82 | 0.3011 | 1.3923 | 0.82 | 0.8012 | 0.1526 | 0.0535 |
216.794 | 91.0 | 2275 | 212.8640 | 0.815 | 0.3006 | 1.3680 | 0.815 | 0.7920 | 0.1443 | 0.0548 |
216.794 | 92.0 | 2300 | 212.8850 | 0.825 | 0.2940 | 1.3317 | 0.825 | 0.8087 | 0.1466 | 0.0548 |
216.794 | 93.0 | 2325 | 212.8843 | 0.825 | 0.3024 | 1.3848 | 0.825 | 0.8027 | 0.1688 | 0.0529 |
216.794 | 94.0 | 2350 | 212.9464 | 0.825 | 0.3013 | 1.3634 | 0.825 | 0.8027 | 0.1607 | 0.0515 |
216.794 | 95.0 | 2375 | 212.9154 | 0.825 | 0.3001 | 1.3262 | 0.825 | 0.8087 | 0.1604 | 0.0539 |
216.794 | 96.0 | 2400 | 212.9131 | 0.825 | 0.2984 | 1.3121 | 0.825 | 0.8027 | 0.1568 | 0.0538 |
216.794 | 97.0 | 2425 | 212.8888 | 0.82 | 0.3003 | 1.3975 | 0.82 | 0.8012 | 0.1614 | 0.0527 |
216.794 | 98.0 | 2450 | 212.8581 | 0.825 | 0.2989 | 1.2911 | 0.825 | 0.8027 | 0.1673 | 0.0542 |
216.794 | 99.0 | 2475 | 212.9360 | 0.83 | 0.2983 | 1.3929 | 0.83 | 0.8118 | 0.1616 | 0.0534 |
216.6176 | 100.0 | 2500 | 212.9255 | 0.825 | 0.2955 | 1.3247 | 0.825 | 0.8027 | 0.1660 | 0.0554 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2