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---
license: apache-2.0
base_model: WinKawaks/vit-small-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dit-base_tobacco-small_tobacco3482_kd
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# dit-base_tobacco-small_tobacco3482_kd
This model is a fine-tuned version of [WinKawaks/vit-small-patch16-224](https://huggingface.co/WinKawaks/vit-small-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5105
- Accuracy: 0.815
- Brier Loss: 0.2790
- Nll: 1.4944
- F1 Micro: 0.815
- F1 Macro: 0.7942
- Ece: 0.1287
- Aurc: 0.0524
## 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 | 2.2378 | 0.17 | 0.8975 | 4.4036 | 0.17 | 0.1418 | 0.2519 | 0.8078 |
| No log | 2.0 | 14 | 1.7484 | 0.38 | 0.7667 | 4.1809 | 0.38 | 0.2513 | 0.3132 | 0.4423 |
| No log | 3.0 | 21 | 1.1417 | 0.55 | 0.5683 | 1.8669 | 0.55 | 0.4592 | 0.2551 | 0.2287 |
| No log | 4.0 | 28 | 0.8020 | 0.685 | 0.4327 | 1.7476 | 0.685 | 0.6393 | 0.2274 | 0.1292 |
| No log | 5.0 | 35 | 0.8347 | 0.645 | 0.4502 | 1.6809 | 0.645 | 0.6306 | 0.1939 | 0.1346 |
| No log | 6.0 | 42 | 0.6546 | 0.735 | 0.3657 | 1.5210 | 0.735 | 0.7191 | 0.1995 | 0.0901 |
| No log | 7.0 | 49 | 0.6447 | 0.76 | 0.3375 | 1.5117 | 0.76 | 0.7450 | 0.1781 | 0.0875 |
| No log | 8.0 | 56 | 0.7089 | 0.775 | 0.3650 | 1.4823 | 0.775 | 0.7554 | 0.2026 | 0.0971 |
| No log | 9.0 | 63 | 0.5721 | 0.785 | 0.3083 | 1.4053 | 0.785 | 0.7633 | 0.1647 | 0.0651 |
| No log | 10.0 | 70 | 0.5953 | 0.795 | 0.3130 | 1.4301 | 0.795 | 0.7971 | 0.1661 | 0.0701 |
| No log | 11.0 | 77 | 0.6352 | 0.79 | 0.3131 | 1.5018 | 0.79 | 0.7607 | 0.1503 | 0.0789 |
| No log | 12.0 | 84 | 0.7999 | 0.735 | 0.3916 | 1.7141 | 0.735 | 0.7065 | 0.2143 | 0.1178 |
| No log | 13.0 | 91 | 0.6602 | 0.8 | 0.3099 | 1.8022 | 0.8000 | 0.7746 | 0.1709 | 0.0805 |
| No log | 14.0 | 98 | 0.6529 | 0.785 | 0.3298 | 1.3607 | 0.785 | 0.7658 | 0.1771 | 0.0858 |
| No log | 15.0 | 105 | 0.6170 | 0.8 | 0.3098 | 1.3676 | 0.8000 | 0.7838 | 0.1630 | 0.0723 |
| No log | 16.0 | 112 | 0.6484 | 0.775 | 0.3342 | 1.2826 | 0.775 | 0.7752 | 0.1837 | 0.0827 |
| No log | 17.0 | 119 | 0.5817 | 0.78 | 0.3019 | 1.6577 | 0.78 | 0.7730 | 0.1566 | 0.0582 |
| No log | 18.0 | 126 | 0.6528 | 0.78 | 0.3376 | 1.5044 | 0.78 | 0.7788 | 0.1687 | 0.0768 |
| No log | 19.0 | 133 | 0.6241 | 0.805 | 0.3038 | 1.3465 | 0.805 | 0.7796 | 0.1498 | 0.0759 |
| No log | 20.0 | 140 | 0.5610 | 0.79 | 0.2948 | 1.4395 | 0.79 | 0.7716 | 0.1515 | 0.0708 |
| No log | 21.0 | 147 | 0.6829 | 0.78 | 0.3241 | 1.3252 | 0.78 | 0.7687 | 0.1782 | 0.0852 |
| No log | 22.0 | 154 | 0.5443 | 0.795 | 0.3117 | 1.4374 | 0.795 | 0.7822 | 0.1730 | 0.0679 |
| No log | 23.0 | 161 | 0.6968 | 0.78 | 0.3474 | 1.7830 | 0.78 | 0.7880 | 0.1745 | 0.0813 |
| No log | 24.0 | 168 | 0.7422 | 0.75 | 0.3639 | 1.5379 | 0.75 | 0.7238 | 0.1982 | 0.0940 |
| No log | 25.0 | 175 | 0.5756 | 0.785 | 0.3150 | 1.4739 | 0.785 | 0.7723 | 0.1615 | 0.0675 |
| No log | 26.0 | 182 | 0.6127 | 0.805 | 0.3036 | 1.5553 | 0.805 | 0.7990 | 0.1416 | 0.0659 |
| No log | 27.0 | 189 | 0.5852 | 0.795 | 0.3104 | 1.5149 | 0.795 | 0.7808 | 0.1583 | 0.0625 |
| No log | 28.0 | 196 | 0.5421 | 0.83 | 0.2808 | 1.4320 | 0.83 | 0.8147 | 0.1475 | 0.0558 |
| No log | 29.0 | 203 | 0.5588 | 0.79 | 0.2888 | 1.5801 | 0.79 | 0.7723 | 0.1465 | 0.0580 |
| No log | 30.0 | 210 | 0.5532 | 0.795 | 0.2892 | 1.5724 | 0.795 | 0.7790 | 0.1453 | 0.0576 |
| No log | 31.0 | 217 | 0.5050 | 0.835 | 0.2685 | 1.4206 | 0.835 | 0.8221 | 0.1459 | 0.0549 |
| No log | 32.0 | 224 | 0.5067 | 0.82 | 0.2762 | 1.4460 | 0.82 | 0.8017 | 0.1494 | 0.0538 |
| No log | 33.0 | 231 | 0.5200 | 0.815 | 0.2798 | 1.5300 | 0.815 | 0.7973 | 0.1442 | 0.0541 |
| No log | 34.0 | 238 | 0.5110 | 0.825 | 0.2802 | 1.6009 | 0.825 | 0.8095 | 0.1462 | 0.0537 |
| No log | 35.0 | 245 | 0.5125 | 0.815 | 0.2804 | 1.5209 | 0.815 | 0.8013 | 0.1555 | 0.0540 |
| No log | 36.0 | 252 | 0.4981 | 0.82 | 0.2728 | 1.4498 | 0.82 | 0.8032 | 0.1557 | 0.0522 |
| No log | 37.0 | 259 | 0.5196 | 0.82 | 0.2796 | 1.5297 | 0.82 | 0.8057 | 0.1396 | 0.0523 |
| No log | 38.0 | 266 | 0.5034 | 0.82 | 0.2755 | 1.4577 | 0.82 | 0.8000 | 0.1449 | 0.0524 |
| No log | 39.0 | 273 | 0.5190 | 0.815 | 0.2810 | 1.5240 | 0.815 | 0.8003 | 0.1516 | 0.0533 |
| No log | 40.0 | 280 | 0.4926 | 0.83 | 0.2697 | 1.4598 | 0.83 | 0.8161 | 0.1248 | 0.0514 |
| No log | 41.0 | 287 | 0.5117 | 0.815 | 0.2808 | 1.5168 | 0.815 | 0.7965 | 0.1306 | 0.0525 |
| No log | 42.0 | 294 | 0.5034 | 0.825 | 0.2721 | 1.5263 | 0.825 | 0.8143 | 0.1389 | 0.0533 |
| No log | 43.0 | 301 | 0.5073 | 0.815 | 0.2762 | 1.5308 | 0.815 | 0.7916 | 0.1452 | 0.0511 |
| No log | 44.0 | 308 | 0.5017 | 0.825 | 0.2751 | 1.5202 | 0.825 | 0.8095 | 0.1473 | 0.0525 |
| No log | 45.0 | 315 | 0.5052 | 0.815 | 0.2783 | 1.5143 | 0.815 | 0.7965 | 0.1451 | 0.0525 |
| No log | 46.0 | 322 | 0.5043 | 0.83 | 0.2743 | 1.5172 | 0.83 | 0.8172 | 0.1481 | 0.0517 |
| No log | 47.0 | 329 | 0.5057 | 0.825 | 0.2767 | 1.5164 | 0.825 | 0.8089 | 0.1325 | 0.0520 |
| No log | 48.0 | 336 | 0.5033 | 0.82 | 0.2752 | 1.5168 | 0.82 | 0.8061 | 0.1430 | 0.0523 |
| No log | 49.0 | 343 | 0.5042 | 0.82 | 0.2755 | 1.5163 | 0.82 | 0.8061 | 0.1394 | 0.0517 |
| No log | 50.0 | 350 | 0.5068 | 0.82 | 0.2767 | 1.5153 | 0.82 | 0.8061 | 0.1471 | 0.0517 |
| No log | 51.0 | 357 | 0.5048 | 0.82 | 0.2759 | 1.5137 | 0.82 | 0.8061 | 0.1419 | 0.0519 |
| No log | 52.0 | 364 | 0.5044 | 0.825 | 0.2759 | 1.5112 | 0.825 | 0.8064 | 0.1342 | 0.0518 |
| No log | 53.0 | 371 | 0.5046 | 0.825 | 0.2756 | 1.5122 | 0.825 | 0.8116 | 0.1388 | 0.0514 |
| No log | 54.0 | 378 | 0.5078 | 0.815 | 0.2777 | 1.5111 | 0.815 | 0.7984 | 0.1442 | 0.0519 |
| No log | 55.0 | 385 | 0.5059 | 0.815 | 0.2767 | 1.5109 | 0.815 | 0.7984 | 0.1351 | 0.0518 |
| No log | 56.0 | 392 | 0.5087 | 0.82 | 0.2779 | 1.5089 | 0.82 | 0.8061 | 0.1391 | 0.0518 |
| No log | 57.0 | 399 | 0.5072 | 0.82 | 0.2771 | 1.5094 | 0.82 | 0.8061 | 0.1339 | 0.0517 |
| No log | 58.0 | 406 | 0.5079 | 0.82 | 0.2776 | 1.5074 | 0.82 | 0.8061 | 0.1366 | 0.0518 |
| No log | 59.0 | 413 | 0.5072 | 0.82 | 0.2771 | 1.5072 | 0.82 | 0.8061 | 0.1308 | 0.0518 |
| No log | 60.0 | 420 | 0.5084 | 0.825 | 0.2776 | 1.5059 | 0.825 | 0.8116 | 0.1303 | 0.0520 |
| No log | 61.0 | 427 | 0.5074 | 0.82 | 0.2772 | 1.5066 | 0.82 | 0.8038 | 0.1244 | 0.0520 |
| No log | 62.0 | 434 | 0.5090 | 0.82 | 0.2781 | 1.5053 | 0.82 | 0.8061 | 0.1367 | 0.0519 |
| No log | 63.0 | 441 | 0.5094 | 0.825 | 0.2779 | 1.5050 | 0.825 | 0.8116 | 0.1305 | 0.0520 |
| No log | 64.0 | 448 | 0.5098 | 0.82 | 0.2782 | 1.5049 | 0.82 | 0.8038 | 0.1314 | 0.0520 |
| No log | 65.0 | 455 | 0.5086 | 0.82 | 0.2780 | 1.5038 | 0.82 | 0.8038 | 0.1249 | 0.0520 |
| No log | 66.0 | 462 | 0.5103 | 0.82 | 0.2787 | 1.5023 | 0.82 | 0.8038 | 0.1222 | 0.0522 |
| No log | 67.0 | 469 | 0.5095 | 0.82 | 0.2782 | 1.5025 | 0.82 | 0.8038 | 0.1228 | 0.0521 |
| No log | 68.0 | 476 | 0.5095 | 0.82 | 0.2783 | 1.5027 | 0.82 | 0.8038 | 0.1330 | 0.0522 |
| No log | 69.0 | 483 | 0.5097 | 0.82 | 0.2785 | 1.5015 | 0.82 | 0.8038 | 0.1228 | 0.0521 |
| No log | 70.0 | 490 | 0.5109 | 0.82 | 0.2788 | 1.5005 | 0.82 | 0.8038 | 0.1322 | 0.0520 |
| No log | 71.0 | 497 | 0.5096 | 0.82 | 0.2784 | 1.5012 | 0.82 | 0.8038 | 0.1320 | 0.0522 |
| 0.1366 | 72.0 | 504 | 0.5095 | 0.82 | 0.2784 | 1.5011 | 0.82 | 0.8038 | 0.1219 | 0.0522 |
| 0.1366 | 73.0 | 511 | 0.5109 | 0.82 | 0.2791 | 1.4998 | 0.82 | 0.8038 | 0.1249 | 0.0523 |
| 0.1366 | 74.0 | 518 | 0.5100 | 0.82 | 0.2786 | 1.5000 | 0.82 | 0.8038 | 0.1219 | 0.0521 |
| 0.1366 | 75.0 | 525 | 0.5096 | 0.82 | 0.2784 | 1.5000 | 0.82 | 0.8038 | 0.1238 | 0.0521 |
| 0.1366 | 76.0 | 532 | 0.5104 | 0.82 | 0.2787 | 1.4988 | 0.82 | 0.8038 | 0.1341 | 0.0523 |
| 0.1366 | 77.0 | 539 | 0.5105 | 0.82 | 0.2788 | 1.4985 | 0.82 | 0.8038 | 0.1340 | 0.0521 |
| 0.1366 | 78.0 | 546 | 0.5103 | 0.82 | 0.2788 | 1.4985 | 0.82 | 0.8038 | 0.1338 | 0.0520 |
| 0.1366 | 79.0 | 553 | 0.5105 | 0.82 | 0.2788 | 1.4983 | 0.82 | 0.8038 | 0.1317 | 0.0522 |
| 0.1366 | 80.0 | 560 | 0.5106 | 0.82 | 0.2789 | 1.4977 | 0.82 | 0.8038 | 0.1337 | 0.0523 |
| 0.1366 | 81.0 | 567 | 0.5108 | 0.82 | 0.2790 | 1.4971 | 0.82 | 0.8038 | 0.1339 | 0.0523 |
| 0.1366 | 82.0 | 574 | 0.5107 | 0.82 | 0.2790 | 1.4970 | 0.82 | 0.8038 | 0.1317 | 0.0521 |
| 0.1366 | 83.0 | 581 | 0.5108 | 0.82 | 0.2790 | 1.4968 | 0.82 | 0.8038 | 0.1339 | 0.0522 |
| 0.1366 | 84.0 | 588 | 0.5105 | 0.82 | 0.2789 | 1.4966 | 0.82 | 0.8038 | 0.1340 | 0.0522 |
| 0.1366 | 85.0 | 595 | 0.5106 | 0.82 | 0.2789 | 1.4961 | 0.82 | 0.8038 | 0.1338 | 0.0523 |
| 0.1366 | 86.0 | 602 | 0.5109 | 0.82 | 0.2790 | 1.4958 | 0.82 | 0.8038 | 0.1336 | 0.0524 |
| 0.1366 | 87.0 | 609 | 0.5105 | 0.815 | 0.2789 | 1.4956 | 0.815 | 0.7942 | 0.1290 | 0.0525 |
| 0.1366 | 88.0 | 616 | 0.5105 | 0.815 | 0.2790 | 1.4954 | 0.815 | 0.7942 | 0.1290 | 0.0525 |
| 0.1366 | 89.0 | 623 | 0.5106 | 0.815 | 0.2790 | 1.4952 | 0.815 | 0.7942 | 0.1290 | 0.0526 |
| 0.1366 | 90.0 | 630 | 0.5106 | 0.82 | 0.2790 | 1.4951 | 0.82 | 0.8038 | 0.1338 | 0.0523 |
| 0.1366 | 91.0 | 637 | 0.5107 | 0.815 | 0.2790 | 1.4949 | 0.815 | 0.7942 | 0.1289 | 0.0526 |
| 0.1366 | 92.0 | 644 | 0.5107 | 0.815 | 0.2790 | 1.4947 | 0.815 | 0.7942 | 0.1289 | 0.0526 |
| 0.1366 | 93.0 | 651 | 0.5107 | 0.815 | 0.2790 | 1.4947 | 0.815 | 0.7942 | 0.1289 | 0.0525 |
| 0.1366 | 94.0 | 658 | 0.5107 | 0.82 | 0.2790 | 1.4946 | 0.82 | 0.8038 | 0.1335 | 0.0523 |
| 0.1366 | 95.0 | 665 | 0.5106 | 0.82 | 0.2790 | 1.4946 | 0.82 | 0.8038 | 0.1335 | 0.0523 |
| 0.1366 | 96.0 | 672 | 0.5105 | 0.815 | 0.2790 | 1.4945 | 0.815 | 0.7942 | 0.1289 | 0.0524 |
| 0.1366 | 97.0 | 679 | 0.5105 | 0.815 | 0.2790 | 1.4945 | 0.815 | 0.7942 | 0.1289 | 0.0524 |
| 0.1366 | 98.0 | 686 | 0.5105 | 0.815 | 0.2790 | 1.4944 | 0.815 | 0.7942 | 0.1289 | 0.0524 |
| 0.1366 | 99.0 | 693 | 0.5105 | 0.815 | 0.2790 | 1.4944 | 0.815 | 0.7942 | 0.1287 | 0.0524 |
| 0.1366 | 100.0 | 700 | 0.5105 | 0.815 | 0.2790 | 1.4944 | 0.815 | 0.7942 | 0.1287 | 0.0524 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.0.dev20231112+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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