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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_CEKD_t2.5_a0.5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dit-base_tobacco-small_tobacco3482_kd_CEKD_t2.5_a0.5
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: 0.6146
- Accuracy: 0.8
- Brier Loss: 0.2784
- Nll: 1.4268
- F1 Micro: 0.8000
- F1 Macro: 0.7846
- Ece: 0.1626
- Aurc: 0.0474
## 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 | 4.1581 | 0.18 | 0.8974 | 4.2254 | 0.18 | 0.1559 | 0.2651 | 0.8061 |
| No log | 2.0 | 14 | 3.2929 | 0.355 | 0.7710 | 4.0541 | 0.3550 | 0.2167 | 0.2742 | 0.4326 |
| No log | 3.0 | 21 | 2.2155 | 0.55 | 0.5837 | 2.0462 | 0.55 | 0.4296 | 0.2323 | 0.2481 |
| No log | 4.0 | 28 | 1.5197 | 0.7 | 0.4370 | 1.7716 | 0.7 | 0.6411 | 0.2342 | 0.1327 |
| No log | 5.0 | 35 | 1.2831 | 0.715 | 0.4289 | 1.7142 | 0.715 | 0.6859 | 0.2047 | 0.1211 |
| No log | 6.0 | 42 | 1.2204 | 0.72 | 0.3989 | 1.6102 | 0.72 | 0.6999 | 0.1961 | 0.1066 |
| No log | 7.0 | 49 | 0.9767 | 0.755 | 0.3317 | 1.5919 | 0.755 | 0.7148 | 0.1724 | 0.0775 |
| No log | 8.0 | 56 | 0.8875 | 0.785 | 0.3049 | 1.4209 | 0.785 | 0.7633 | 0.1478 | 0.0716 |
| No log | 9.0 | 63 | 0.9311 | 0.79 | 0.3185 | 1.5420 | 0.79 | 0.7474 | 0.1645 | 0.0741 |
| No log | 10.0 | 70 | 0.8116 | 0.835 | 0.2672 | 1.5127 | 0.835 | 0.8232 | 0.1463 | 0.0563 |
| No log | 11.0 | 77 | 0.8315 | 0.805 | 0.3054 | 1.6275 | 0.805 | 0.7897 | 0.1695 | 0.0618 |
| No log | 12.0 | 84 | 0.7678 | 0.815 | 0.2917 | 1.5009 | 0.815 | 0.8012 | 0.1469 | 0.0542 |
| No log | 13.0 | 91 | 0.7249 | 0.81 | 0.2816 | 1.4685 | 0.81 | 0.7880 | 0.1437 | 0.0576 |
| No log | 14.0 | 98 | 0.8116 | 0.815 | 0.2894 | 1.5975 | 0.815 | 0.7941 | 0.1481 | 0.0604 |
| No log | 15.0 | 105 | 0.7985 | 0.81 | 0.3098 | 1.4721 | 0.81 | 0.7819 | 0.1646 | 0.0662 |
| No log | 16.0 | 112 | 0.6839 | 0.815 | 0.2781 | 1.4357 | 0.815 | 0.7992 | 0.1589 | 0.0529 |
| No log | 17.0 | 119 | 0.6590 | 0.82 | 0.2670 | 1.4487 | 0.82 | 0.8061 | 0.1336 | 0.0461 |
| No log | 18.0 | 126 | 0.7253 | 0.81 | 0.2938 | 1.5163 | 0.81 | 0.7951 | 0.1617 | 0.0558 |
| No log | 19.0 | 133 | 0.6935 | 0.795 | 0.2949 | 1.4516 | 0.795 | 0.7758 | 0.1736 | 0.0531 |
| No log | 20.0 | 140 | 0.6991 | 0.795 | 0.2875 | 1.3932 | 0.795 | 0.7735 | 0.1584 | 0.0519 |
| No log | 21.0 | 147 | 0.7059 | 0.815 | 0.2966 | 1.5011 | 0.815 | 0.7927 | 0.1579 | 0.0565 |
| No log | 22.0 | 154 | 0.6754 | 0.79 | 0.2896 | 1.4549 | 0.79 | 0.7742 | 0.1534 | 0.0531 |
| No log | 23.0 | 161 | 0.6981 | 0.785 | 0.2989 | 1.4261 | 0.785 | 0.7705 | 0.1490 | 0.0530 |
| No log | 24.0 | 168 | 0.6503 | 0.805 | 0.2842 | 1.4998 | 0.805 | 0.7885 | 0.1415 | 0.0512 |
| No log | 25.0 | 175 | 0.6680 | 0.79 | 0.2891 | 1.4228 | 0.79 | 0.7742 | 0.1504 | 0.0519 |
| No log | 26.0 | 182 | 0.6835 | 0.81 | 0.2948 | 1.4400 | 0.81 | 0.7944 | 0.1545 | 0.0516 |
| No log | 27.0 | 189 | 0.6495 | 0.81 | 0.2846 | 1.4433 | 0.81 | 0.7868 | 0.1552 | 0.0503 |
| No log | 28.0 | 196 | 0.6450 | 0.81 | 0.2851 | 1.4037 | 0.81 | 0.7913 | 0.1476 | 0.0498 |
| No log | 29.0 | 203 | 0.6634 | 0.815 | 0.2861 | 1.4186 | 0.815 | 0.7966 | 0.1397 | 0.0521 |
| No log | 30.0 | 210 | 0.6212 | 0.805 | 0.2739 | 1.4265 | 0.805 | 0.7902 | 0.1444 | 0.0482 |
| No log | 31.0 | 217 | 0.6271 | 0.815 | 0.2800 | 1.4392 | 0.815 | 0.7986 | 0.1370 | 0.0494 |
| No log | 32.0 | 224 | 0.6256 | 0.8 | 0.2786 | 1.3677 | 0.8000 | 0.7811 | 0.1454 | 0.0496 |
| No log | 33.0 | 231 | 0.6219 | 0.805 | 0.2779 | 1.4276 | 0.805 | 0.7857 | 0.1580 | 0.0465 |
| No log | 34.0 | 238 | 0.6203 | 0.81 | 0.2779 | 1.4392 | 0.81 | 0.7914 | 0.1275 | 0.0470 |
| No log | 35.0 | 245 | 0.6193 | 0.81 | 0.2793 | 1.4258 | 0.81 | 0.7934 | 0.1438 | 0.0483 |
| No log | 36.0 | 252 | 0.6261 | 0.83 | 0.2743 | 1.4227 | 0.83 | 0.8098 | 0.1482 | 0.0501 |
| No log | 37.0 | 259 | 0.6190 | 0.815 | 0.2776 | 1.4301 | 0.815 | 0.7977 | 0.1446 | 0.0484 |
| No log | 38.0 | 266 | 0.6210 | 0.805 | 0.2867 | 1.4958 | 0.805 | 0.7878 | 0.1477 | 0.0496 |
| No log | 39.0 | 273 | 0.5974 | 0.805 | 0.2771 | 1.5068 | 0.805 | 0.7901 | 0.1381 | 0.0476 |
| No log | 40.0 | 280 | 0.6224 | 0.8 | 0.2869 | 1.4325 | 0.8000 | 0.7869 | 0.1443 | 0.0472 |
| No log | 41.0 | 287 | 0.6178 | 0.805 | 0.2796 | 1.4316 | 0.805 | 0.7912 | 0.1454 | 0.0471 |
| No log | 42.0 | 294 | 0.6194 | 0.825 | 0.2765 | 1.5001 | 0.825 | 0.8059 | 0.1401 | 0.0474 |
| No log | 43.0 | 301 | 0.6224 | 0.805 | 0.2769 | 1.4268 | 0.805 | 0.7888 | 0.1398 | 0.0493 |
| No log | 44.0 | 308 | 0.6265 | 0.8 | 0.2819 | 1.4401 | 0.8000 | 0.7846 | 0.1422 | 0.0481 |
| No log | 45.0 | 315 | 0.6275 | 0.8 | 0.2819 | 1.4206 | 0.8000 | 0.7847 | 0.1465 | 0.0487 |
| No log | 46.0 | 322 | 0.6173 | 0.805 | 0.2806 | 1.3618 | 0.805 | 0.7870 | 0.1383 | 0.0478 |
| No log | 47.0 | 329 | 0.6177 | 0.81 | 0.2804 | 1.4988 | 0.81 | 0.7906 | 0.1468 | 0.0488 |
| No log | 48.0 | 336 | 0.6175 | 0.81 | 0.2788 | 1.4356 | 0.81 | 0.7917 | 0.1460 | 0.0476 |
| No log | 49.0 | 343 | 0.6209 | 0.81 | 0.2775 | 1.4290 | 0.81 | 0.7925 | 0.1603 | 0.0478 |
| No log | 50.0 | 350 | 0.6244 | 0.815 | 0.2780 | 1.3662 | 0.815 | 0.7974 | 0.1322 | 0.0480 |
| No log | 51.0 | 357 | 0.6176 | 0.81 | 0.2777 | 1.4307 | 0.81 | 0.7941 | 0.1258 | 0.0478 |
| No log | 52.0 | 364 | 0.6150 | 0.805 | 0.2774 | 1.4310 | 0.805 | 0.7896 | 0.1369 | 0.0477 |
| No log | 53.0 | 371 | 0.6164 | 0.81 | 0.2772 | 1.4298 | 0.81 | 0.7941 | 0.1391 | 0.0479 |
| No log | 54.0 | 378 | 0.6137 | 0.81 | 0.2766 | 1.4291 | 0.81 | 0.7928 | 0.1358 | 0.0474 |
| No log | 55.0 | 385 | 0.6163 | 0.81 | 0.2776 | 1.4298 | 0.81 | 0.7928 | 0.1278 | 0.0475 |
| No log | 56.0 | 392 | 0.6148 | 0.81 | 0.2776 | 1.4286 | 0.81 | 0.7928 | 0.1480 | 0.0471 |
| No log | 57.0 | 399 | 0.6154 | 0.81 | 0.2773 | 1.4290 | 0.81 | 0.7928 | 0.1485 | 0.0474 |
| No log | 58.0 | 406 | 0.6143 | 0.8 | 0.2781 | 1.4281 | 0.8000 | 0.7852 | 0.1405 | 0.0473 |
| No log | 59.0 | 413 | 0.6158 | 0.805 | 0.2785 | 1.4295 | 0.805 | 0.7899 | 0.1455 | 0.0473 |
| No log | 60.0 | 420 | 0.6146 | 0.805 | 0.2774 | 1.4310 | 0.805 | 0.7899 | 0.1346 | 0.0472 |
| No log | 61.0 | 427 | 0.6154 | 0.805 | 0.2780 | 1.4292 | 0.805 | 0.7899 | 0.1451 | 0.0472 |
| No log | 62.0 | 434 | 0.6148 | 0.805 | 0.2780 | 1.4304 | 0.805 | 0.7905 | 0.1543 | 0.0473 |
| No log | 63.0 | 441 | 0.6150 | 0.8 | 0.2783 | 1.4284 | 0.8000 | 0.7846 | 0.1502 | 0.0473 |
| No log | 64.0 | 448 | 0.6143 | 0.805 | 0.2780 | 1.4294 | 0.805 | 0.7899 | 0.1453 | 0.0470 |
| No log | 65.0 | 455 | 0.6152 | 0.805 | 0.2782 | 1.4298 | 0.805 | 0.7899 | 0.1373 | 0.0469 |
| No log | 66.0 | 462 | 0.6148 | 0.8 | 0.2781 | 1.4287 | 0.8000 | 0.7852 | 0.1492 | 0.0475 |
| No log | 67.0 | 469 | 0.6134 | 0.805 | 0.2776 | 1.4286 | 0.805 | 0.7899 | 0.1526 | 0.0470 |
| No log | 68.0 | 476 | 0.6150 | 0.8 | 0.2785 | 1.4270 | 0.8000 | 0.7846 | 0.1497 | 0.0474 |
| No log | 69.0 | 483 | 0.6145 | 0.8 | 0.2783 | 1.4281 | 0.8000 | 0.7846 | 0.1483 | 0.0471 |
| No log | 70.0 | 490 | 0.6145 | 0.805 | 0.2778 | 1.4292 | 0.805 | 0.7899 | 0.1472 | 0.0471 |
| No log | 71.0 | 497 | 0.6143 | 0.805 | 0.2779 | 1.4284 | 0.805 | 0.7899 | 0.1529 | 0.0470 |
| 0.2616 | 72.0 | 504 | 0.6148 | 0.805 | 0.2780 | 1.4276 | 0.805 | 0.7899 | 0.1414 | 0.0471 |
| 0.2616 | 73.0 | 511 | 0.6147 | 0.8 | 0.2781 | 1.4285 | 0.8000 | 0.7852 | 0.1400 | 0.0473 |
| 0.2616 | 74.0 | 518 | 0.6147 | 0.8 | 0.2783 | 1.4281 | 0.8000 | 0.7846 | 0.1501 | 0.0473 |
| 0.2616 | 75.0 | 525 | 0.6150 | 0.8 | 0.2784 | 1.4269 | 0.8000 | 0.7846 | 0.1417 | 0.0473 |
| 0.2616 | 76.0 | 532 | 0.6143 | 0.805 | 0.2782 | 1.4273 | 0.805 | 0.7899 | 0.1524 | 0.0470 |
| 0.2616 | 77.0 | 539 | 0.6147 | 0.805 | 0.2782 | 1.4277 | 0.805 | 0.7899 | 0.1526 | 0.0470 |
| 0.2616 | 78.0 | 546 | 0.6149 | 0.8 | 0.2785 | 1.4277 | 0.8000 | 0.7846 | 0.1572 | 0.0474 |
| 0.2616 | 79.0 | 553 | 0.6147 | 0.805 | 0.2782 | 1.4276 | 0.805 | 0.7899 | 0.1529 | 0.0471 |
| 0.2616 | 80.0 | 560 | 0.6145 | 0.805 | 0.2783 | 1.4278 | 0.805 | 0.7899 | 0.1527 | 0.0471 |
| 0.2616 | 81.0 | 567 | 0.6147 | 0.8 | 0.2783 | 1.4277 | 0.8000 | 0.7846 | 0.1483 | 0.0472 |
| 0.2616 | 82.0 | 574 | 0.6146 | 0.8 | 0.2783 | 1.4275 | 0.8000 | 0.7846 | 0.1623 | 0.0473 |
| 0.2616 | 83.0 | 581 | 0.6145 | 0.8 | 0.2783 | 1.4274 | 0.8000 | 0.7846 | 0.1571 | 0.0473 |
| 0.2616 | 84.0 | 588 | 0.6146 | 0.8 | 0.2782 | 1.4276 | 0.8000 | 0.7846 | 0.1538 | 0.0473 |
| 0.2616 | 85.0 | 595 | 0.6146 | 0.805 | 0.2783 | 1.4274 | 0.805 | 0.7899 | 0.1493 | 0.0471 |
| 0.2616 | 86.0 | 602 | 0.6147 | 0.8 | 0.2784 | 1.4269 | 0.8000 | 0.7846 | 0.1627 | 0.0473 |
| 0.2616 | 87.0 | 609 | 0.6146 | 0.8 | 0.2783 | 1.4270 | 0.8000 | 0.7846 | 0.1623 | 0.0472 |
| 0.2616 | 88.0 | 616 | 0.6145 | 0.805 | 0.2783 | 1.4272 | 0.805 | 0.7899 | 0.1579 | 0.0470 |
| 0.2616 | 89.0 | 623 | 0.6146 | 0.8 | 0.2784 | 1.4272 | 0.8000 | 0.7846 | 0.1627 | 0.0474 |
| 0.2616 | 90.0 | 630 | 0.6147 | 0.8 | 0.2783 | 1.4270 | 0.8000 | 0.7846 | 0.1536 | 0.0473 |
| 0.2616 | 91.0 | 637 | 0.6147 | 0.8 | 0.2784 | 1.4268 | 0.8000 | 0.7846 | 0.1627 | 0.0475 |
| 0.2616 | 92.0 | 644 | 0.6145 | 0.805 | 0.2783 | 1.4268 | 0.805 | 0.7899 | 0.1582 | 0.0471 |
| 0.2616 | 93.0 | 651 | 0.6145 | 0.8 | 0.2784 | 1.4269 | 0.8000 | 0.7846 | 0.1626 | 0.0474 |
| 0.2616 | 94.0 | 658 | 0.6146 | 0.8 | 0.2784 | 1.4268 | 0.8000 | 0.7846 | 0.1626 | 0.0473 |
| 0.2616 | 95.0 | 665 | 0.6147 | 0.8 | 0.2784 | 1.4268 | 0.8000 | 0.7846 | 0.1626 | 0.0473 |
| 0.2616 | 96.0 | 672 | 0.6146 | 0.8 | 0.2784 | 1.4269 | 0.8000 | 0.7846 | 0.1626 | 0.0474 |
| 0.2616 | 97.0 | 679 | 0.6146 | 0.8 | 0.2784 | 1.4269 | 0.8000 | 0.7846 | 0.1626 | 0.0474 |
| 0.2616 | 98.0 | 686 | 0.6146 | 0.8 | 0.2784 | 1.4269 | 0.8000 | 0.7846 | 0.1626 | 0.0474 |
| 0.2616 | 99.0 | 693 | 0.6146 | 0.8 | 0.2784 | 1.4268 | 0.8000 | 0.7846 | 0.1626 | 0.0474 |
| 0.2616 | 100.0 | 700 | 0.6146 | 0.8 | 0.2784 | 1.4268 | 0.8000 | 0.7846 | 0.1626 | 0.0474 |
### 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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