--- license: apache-2.0 base_model: WinKawaks/vit-tiny-patch16-224 tags: - generated_from_trainer metrics: - accuracy model-index: - name: dit-base_tobacco-tiny_tobacco3482_hint results: [] --- # dit-base_tobacco-tiny_tobacco3482_hint This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1196 - Accuracy: 0.805 - Brier Loss: 0.3299 - Nll: 1.3687 - F1 Micro: 0.805 - F1 Macro: 0.7917 - Ece: 0.1606 - Aurc: 0.0741 ## 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: 128 - eval_batch_size: 128 - 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 | 7 | 3.7183 | 0.225 | 0.9191 | 7.9210 | 0.225 | 0.1037 | 0.3197 | 0.7539 | | No log | 2.0 | 14 | 3.2602 | 0.365 | 0.7808 | 4.4817 | 0.3650 | 0.2558 | 0.2908 | 0.5116 | | No log | 3.0 | 21 | 2.8475 | 0.53 | 0.6305 | 2.7026 | 0.53 | 0.4263 | 0.2496 | 0.2812 | | No log | 4.0 | 28 | 2.6118 | 0.575 | 0.5382 | 1.8007 | 0.575 | 0.5478 | 0.2435 | 0.2022 | | No log | 5.0 | 35 | 2.4289 | 0.66 | 0.4404 | 1.6436 | 0.66 | 0.6317 | 0.2124 | 0.1236 | | No log | 6.0 | 42 | 2.4007 | 0.69 | 0.4123 | 1.9255 | 0.69 | 0.6896 | 0.2038 | 0.1195 | | No log | 7.0 | 49 | 2.3239 | 0.745 | 0.3775 | 1.9428 | 0.745 | 0.7365 | 0.1838 | 0.0957 | | No log | 8.0 | 56 | 2.3109 | 0.735 | 0.3660 | 1.6472 | 0.735 | 0.7370 | 0.1729 | 0.0842 | | No log | 9.0 | 63 | 2.3263 | 0.74 | 0.3867 | 1.5935 | 0.74 | 0.7422 | 0.1803 | 0.0944 | | No log | 10.0 | 70 | 2.3878 | 0.735 | 0.4037 | 1.6604 | 0.735 | 0.7039 | 0.2057 | 0.0909 | | No log | 11.0 | 77 | 2.5009 | 0.715 | 0.4220 | 1.8526 | 0.715 | 0.6918 | 0.2184 | 0.1017 | | No log | 12.0 | 84 | 2.5428 | 0.72 | 0.4169 | 1.8799 | 0.72 | 0.6894 | 0.2000 | 0.0979 | | No log | 13.0 | 91 | 2.5197 | 0.765 | 0.3884 | 1.8802 | 0.765 | 0.7268 | 0.1895 | 0.0933 | | No log | 14.0 | 98 | 2.4928 | 0.725 | 0.4147 | 1.6096 | 0.7250 | 0.6923 | 0.2078 | 0.0940 | | No log | 15.0 | 105 | 2.4172 | 0.765 | 0.3748 | 1.6754 | 0.765 | 0.7317 | 0.1874 | 0.0824 | | No log | 16.0 | 112 | 2.4116 | 0.76 | 0.3873 | 1.4155 | 0.76 | 0.7280 | 0.1972 | 0.0890 | | No log | 17.0 | 119 | 2.9196 | 0.73 | 0.4500 | 1.8493 | 0.7300 | 0.7220 | 0.2290 | 0.1657 | | No log | 18.0 | 126 | 2.5815 | 0.765 | 0.4175 | 2.0326 | 0.765 | 0.7467 | 0.2125 | 0.0990 | | No log | 19.0 | 133 | 2.7076 | 0.735 | 0.4475 | 1.8526 | 0.735 | 0.7152 | 0.2062 | 0.1049 | | No log | 20.0 | 140 | 2.6951 | 0.71 | 0.4709 | 2.0521 | 0.7100 | 0.7258 | 0.2380 | 0.1188 | | No log | 21.0 | 147 | 2.4037 | 0.765 | 0.4013 | 1.8740 | 0.765 | 0.7691 | 0.2009 | 0.0949 | | No log | 22.0 | 154 | 2.6585 | 0.73 | 0.4303 | 2.0299 | 0.7300 | 0.7170 | 0.2110 | 0.1004 | | No log | 23.0 | 161 | 2.4320 | 0.75 | 0.3950 | 1.8720 | 0.75 | 0.7340 | 0.2004 | 0.0895 | | No log | 24.0 | 168 | 2.4891 | 0.74 | 0.4199 | 1.6458 | 0.74 | 0.7458 | 0.2227 | 0.1128 | | No log | 25.0 | 175 | 2.6550 | 0.705 | 0.4833 | 1.7755 | 0.705 | 0.7042 | 0.2478 | 0.1145 | | No log | 26.0 | 182 | 2.3191 | 0.765 | 0.3965 | 1.6941 | 0.765 | 0.7415 | 0.1954 | 0.0731 | | No log | 27.0 | 189 | 2.3000 | 0.785 | 0.3763 | 1.3143 | 0.785 | 0.7416 | 0.2026 | 0.0712 | | No log | 28.0 | 196 | 2.2047 | 0.78 | 0.3409 | 1.4818 | 0.78 | 0.7694 | 0.1759 | 0.0688 | | No log | 29.0 | 203 | 2.3587 | 0.77 | 0.3781 | 1.6779 | 0.7700 | 0.7571 | 0.1937 | 0.0766 | | No log | 30.0 | 210 | 2.5027 | 0.75 | 0.4400 | 1.8454 | 0.75 | 0.7338 | 0.2232 | 0.0817 | | No log | 31.0 | 217 | 2.4092 | 0.77 | 0.3899 | 1.5010 | 0.7700 | 0.7498 | 0.1987 | 0.0710 | | No log | 32.0 | 224 | 2.7655 | 0.74 | 0.4520 | 2.0720 | 0.74 | 0.7177 | 0.2266 | 0.0855 | | No log | 33.0 | 231 | 2.3814 | 0.76 | 0.3979 | 1.4053 | 0.76 | 0.7352 | 0.1982 | 0.0754 | | No log | 34.0 | 238 | 2.3946 | 0.775 | 0.3790 | 1.6969 | 0.775 | 0.7387 | 0.1908 | 0.0876 | | No log | 35.0 | 245 | 2.5158 | 0.775 | 0.4064 | 1.4329 | 0.775 | 0.7428 | 0.2068 | 0.0929 | | No log | 36.0 | 252 | 2.4920 | 0.75 | 0.4281 | 1.5724 | 0.75 | 0.7470 | 0.2161 | 0.1028 | | No log | 37.0 | 259 | 2.4541 | 0.765 | 0.3842 | 1.5272 | 0.765 | 0.7163 | 0.1918 | 0.0853 | | No log | 38.0 | 266 | 2.3785 | 0.82 | 0.3319 | 1.6360 | 0.82 | 0.7944 | 0.1732 | 0.0811 | | No log | 39.0 | 273 | 2.3721 | 0.77 | 0.3831 | 1.2724 | 0.7700 | 0.7649 | 0.1880 | 0.0818 | | No log | 40.0 | 280 | 2.5684 | 0.795 | 0.3494 | 1.7291 | 0.795 | 0.7724 | 0.1771 | 0.1126 | | No log | 41.0 | 287 | 2.4835 | 0.78 | 0.3799 | 1.7700 | 0.78 | 0.7594 | 0.2024 | 0.0821 | | No log | 42.0 | 294 | 2.4690 | 0.795 | 0.3678 | 1.6379 | 0.795 | 0.7804 | 0.1836 | 0.0840 | | No log | 43.0 | 301 | 2.3069 | 0.77 | 0.3809 | 1.4970 | 0.7700 | 0.7621 | 0.1807 | 0.0784 | | No log | 44.0 | 308 | 2.4424 | 0.795 | 0.3558 | 1.7162 | 0.795 | 0.7857 | 0.1879 | 0.0667 | | No log | 45.0 | 315 | 2.0018 | 0.86 | 0.2387 | 1.4924 | 0.8600 | 0.8558 | 0.1180 | 0.0526 | | No log | 46.0 | 322 | 2.4174 | 0.785 | 0.3593 | 1.7688 | 0.785 | 0.7662 | 0.1859 | 0.0773 | | No log | 47.0 | 329 | 2.1816 | 0.84 | 0.2862 | 1.5093 | 0.8400 | 0.8230 | 0.1459 | 0.0679 | | No log | 48.0 | 336 | 2.3006 | 0.78 | 0.3601 | 1.7675 | 0.78 | 0.7496 | 0.1847 | 0.0752 | | No log | 49.0 | 343 | 2.2952 | 0.81 | 0.3231 | 1.4851 | 0.81 | 0.7865 | 0.1691 | 0.0656 | | No log | 50.0 | 350 | 2.1346 | 0.8 | 0.3132 | 1.4625 | 0.8000 | 0.7937 | 0.1660 | 0.0789 | | No log | 51.0 | 357 | 2.2935 | 0.81 | 0.3383 | 1.5764 | 0.81 | 0.7914 | 0.1770 | 0.0717 | | No log | 52.0 | 364 | 2.1792 | 0.825 | 0.3116 | 1.5652 | 0.825 | 0.8163 | 0.1454 | 0.0654 | | No log | 53.0 | 371 | 2.1231 | 0.81 | 0.3066 | 1.3012 | 0.81 | 0.8062 | 0.1552 | 0.0604 | | No log | 54.0 | 378 | 1.9712 | 0.825 | 0.2854 | 1.2891 | 0.825 | 0.8137 | 0.1430 | 0.0521 | | No log | 55.0 | 385 | 2.0133 | 0.825 | 0.2839 | 1.3994 | 0.825 | 0.8086 | 0.1433 | 0.0560 | | No log | 56.0 | 392 | 1.9978 | 0.835 | 0.2800 | 1.4348 | 0.835 | 0.8232 | 0.1415 | 0.0573 | | No log | 57.0 | 399 | 1.9847 | 0.83 | 0.2825 | 1.3907 | 0.83 | 0.8153 | 0.1421 | 0.0560 | | No log | 58.0 | 406 | 1.9892 | 0.83 | 0.2832 | 1.4502 | 0.83 | 0.8153 | 0.1503 | 0.0566 | | No log | 59.0 | 413 | 1.9848 | 0.83 | 0.2851 | 1.4506 | 0.83 | 0.8156 | 0.1462 | 0.0560 | | No log | 60.0 | 420 | 1.9871 | 0.835 | 0.2910 | 1.4527 | 0.835 | 0.8191 | 0.1608 | 0.0566 | | No log | 61.0 | 427 | 1.9914 | 0.825 | 0.2932 | 1.4490 | 0.825 | 0.8095 | 0.1464 | 0.0587 | | No log | 62.0 | 434 | 1.9908 | 0.825 | 0.2958 | 1.4459 | 0.825 | 0.8095 | 0.1493 | 0.0597 | | No log | 63.0 | 441 | 1.9954 | 0.825 | 0.3012 | 1.4480 | 0.825 | 0.8095 | 0.1469 | 0.0606 | | No log | 64.0 | 448 | 2.0111 | 0.82 | 0.3050 | 1.4487 | 0.82 | 0.8026 | 0.1507 | 0.0619 | | No log | 65.0 | 455 | 2.0212 | 0.82 | 0.3046 | 1.4469 | 0.82 | 0.8026 | 0.1604 | 0.0634 | | No log | 66.0 | 462 | 2.0170 | 0.82 | 0.3059 | 1.4443 | 0.82 | 0.8040 | 0.1539 | 0.0639 | | No log | 67.0 | 469 | 2.0170 | 0.815 | 0.3056 | 1.4496 | 0.815 | 0.8019 | 0.1534 | 0.0643 | | No log | 68.0 | 476 | 2.0316 | 0.82 | 0.3115 | 1.4522 | 0.82 | 0.8026 | 0.1606 | 0.0645 | | No log | 69.0 | 483 | 2.0335 | 0.805 | 0.3132 | 1.3831 | 0.805 | 0.7855 | 0.1607 | 0.0654 | | No log | 70.0 | 490 | 2.0362 | 0.815 | 0.3106 | 1.3834 | 0.815 | 0.7989 | 0.1614 | 0.0655 | | No log | 71.0 | 497 | 2.0318 | 0.815 | 0.3105 | 1.3893 | 0.815 | 0.7947 | 0.1541 | 0.0662 | | 1.3661 | 72.0 | 504 | 2.0434 | 0.815 | 0.3135 | 1.4473 | 0.815 | 0.7955 | 0.1579 | 0.0653 | | 1.3661 | 73.0 | 511 | 2.0517 | 0.81 | 0.3139 | 1.3838 | 0.81 | 0.7917 | 0.1564 | 0.0680 | | 1.3661 | 74.0 | 518 | 2.0594 | 0.82 | 0.3162 | 1.3783 | 0.82 | 0.7975 | 0.1626 | 0.0681 | | 1.3661 | 75.0 | 525 | 2.0628 | 0.815 | 0.3210 | 1.3752 | 0.815 | 0.7944 | 0.1598 | 0.0706 | | 1.3661 | 76.0 | 532 | 2.0605 | 0.81 | 0.3158 | 1.3711 | 0.81 | 0.7886 | 0.1639 | 0.0684 | | 1.3661 | 77.0 | 539 | 2.0718 | 0.815 | 0.3187 | 1.3860 | 0.815 | 0.7944 | 0.1710 | 0.0705 | | 1.3661 | 78.0 | 546 | 2.0749 | 0.815 | 0.3168 | 1.3658 | 0.815 | 0.7958 | 0.1569 | 0.0713 | | 1.3661 | 79.0 | 553 | 2.0796 | 0.83 | 0.3188 | 1.3016 | 0.83 | 0.8147 | 0.1646 | 0.0722 | | 1.3661 | 80.0 | 560 | 2.0746 | 0.81 | 0.3210 | 1.3758 | 0.81 | 0.7916 | 0.1580 | 0.0729 | | 1.3661 | 81.0 | 567 | 2.0819 | 0.815 | 0.3194 | 1.3686 | 0.815 | 0.7913 | 0.1576 | 0.0722 | | 1.3661 | 82.0 | 574 | 2.0866 | 0.825 | 0.3182 | 1.3627 | 0.825 | 0.8085 | 0.1602 | 0.0718 | | 1.3661 | 83.0 | 581 | 2.0942 | 0.815 | 0.3246 | 1.3249 | 0.815 | 0.8008 | 0.1591 | 0.0727 | | 1.3661 | 84.0 | 588 | 2.0938 | 0.815 | 0.3246 | 1.3680 | 0.815 | 0.7984 | 0.1848 | 0.0727 | | 1.3661 | 85.0 | 595 | 2.0912 | 0.82 | 0.3222 | 1.3662 | 0.82 | 0.8012 | 0.1594 | 0.0702 | | 1.3661 | 86.0 | 602 | 2.0941 | 0.82 | 0.3234 | 1.3764 | 0.82 | 0.8012 | 0.1576 | 0.0738 | | 1.3661 | 87.0 | 609 | 2.1037 | 0.8 | 0.3304 | 1.3821 | 0.8000 | 0.7821 | 0.1599 | 0.0740 | | 1.3661 | 88.0 | 616 | 2.1098 | 0.805 | 0.3288 | 1.3587 | 0.805 | 0.7932 | 0.1678 | 0.0718 | | 1.3661 | 89.0 | 623 | 2.1119 | 0.81 | 0.3276 | 1.3636 | 0.81 | 0.7945 | 0.1622 | 0.0728 | | 1.3661 | 90.0 | 630 | 2.1078 | 0.805 | 0.3279 | 1.3641 | 0.805 | 0.7914 | 0.1734 | 0.0737 | | 1.3661 | 91.0 | 637 | 2.1110 | 0.8 | 0.3296 | 1.3686 | 0.8000 | 0.7879 | 0.1636 | 0.0744 | | 1.3661 | 92.0 | 644 | 2.1150 | 0.8 | 0.3317 | 1.3685 | 0.8000 | 0.7879 | 0.1730 | 0.0742 | | 1.3661 | 93.0 | 651 | 2.1146 | 0.8 | 0.3303 | 1.3693 | 0.8000 | 0.7881 | 0.1631 | 0.0742 | | 1.3661 | 94.0 | 658 | 2.1153 | 0.805 | 0.3292 | 1.3657 | 0.805 | 0.7917 | 0.1676 | 0.0734 | | 1.3661 | 95.0 | 665 | 2.1188 | 0.805 | 0.3298 | 1.3683 | 0.805 | 0.7917 | 0.1690 | 0.0735 | | 1.3661 | 96.0 | 672 | 2.1183 | 0.805 | 0.3291 | 1.3691 | 0.805 | 0.7914 | 0.1687 | 0.0742 | | 1.3661 | 97.0 | 679 | 2.1155 | 0.81 | 0.3271 | 1.3664 | 0.81 | 0.7942 | 0.1599 | 0.0743 | | 1.3661 | 98.0 | 686 | 2.1183 | 0.805 | 0.3285 | 1.3673 | 0.805 | 0.7914 | 0.1638 | 0.0740 | | 1.3661 | 99.0 | 693 | 2.1179 | 0.805 | 0.3297 | 1.3686 | 0.805 | 0.7917 | 0.1613 | 0.0741 | | 1.3661 | 100.0 | 700 | 2.1196 | 0.805 | 0.3299 | 1.3687 | 0.805 | 0.7917 | 0.1606 | 0.0741 | ### Framework versions - Transformers 4.36.0.dev0 - Pytorch 2.2.0.dev20231112+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1