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---
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_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-tiny_tobacco3482_kd
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: 0.4787
- Accuracy: 0.815
- Brier Loss: 0.2625
- Nll: 1.3204
- F1 Micro: 0.815
- F1 Macro: 0.8058
- Ece: 0.1408
- Aurc: 0.0457
## 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 | 2.2200 | 0.225 | 0.9173 | 7.9176 | 0.225 | 0.1043 | 0.3247 | 0.7528 |
| No log | 2.0 | 14 | 1.7791 | 0.37 | 0.7982 | 4.5330 | 0.37 | 0.2759 | 0.2753 | 0.6029 |
| No log | 3.0 | 21 | 1.3855 | 0.485 | 0.6628 | 2.8048 | 0.485 | 0.4006 | 0.2716 | 0.3216 |
| No log | 4.0 | 28 | 1.0594 | 0.575 | 0.5416 | 1.7471 | 0.575 | 0.5296 | 0.2314 | 0.2052 |
| No log | 5.0 | 35 | 0.8946 | 0.645 | 0.4739 | 1.6979 | 0.645 | 0.6319 | 0.2168 | 0.1476 |
| No log | 6.0 | 42 | 0.8969 | 0.66 | 0.4688 | 1.7181 | 0.66 | 0.6621 | 0.1985 | 0.1439 |
| No log | 7.0 | 49 | 0.7466 | 0.72 | 0.3937 | 1.5484 | 0.72 | 0.7222 | 0.2135 | 0.1079 |
| No log | 8.0 | 56 | 0.7075 | 0.725 | 0.3753 | 1.4585 | 0.7250 | 0.7100 | 0.2029 | 0.0894 |
| No log | 9.0 | 63 | 0.9838 | 0.695 | 0.4504 | 2.0243 | 0.695 | 0.6681 | 0.2306 | 0.1204 |
| No log | 10.0 | 70 | 0.7683 | 0.73 | 0.3867 | 1.5378 | 0.7300 | 0.7388 | 0.1699 | 0.0902 |
| No log | 11.0 | 77 | 0.7114 | 0.755 | 0.3524 | 1.5684 | 0.755 | 0.7296 | 0.1687 | 0.0742 |
| No log | 12.0 | 84 | 0.8151 | 0.76 | 0.3728 | 1.4721 | 0.76 | 0.7336 | 0.1863 | 0.0936 |
| No log | 13.0 | 91 | 0.8346 | 0.77 | 0.3524 | 1.9540 | 0.7700 | 0.7528 | 0.1691 | 0.0790 |
| No log | 14.0 | 98 | 0.7822 | 0.735 | 0.3898 | 1.6873 | 0.735 | 0.7215 | 0.2025 | 0.0860 |
| No log | 15.0 | 105 | 0.7400 | 0.765 | 0.3580 | 1.5692 | 0.765 | 0.7167 | 0.1765 | 0.0809 |
| No log | 16.0 | 112 | 0.8296 | 0.71 | 0.4027 | 1.5508 | 0.7100 | 0.6837 | 0.2185 | 0.0963 |
| No log | 17.0 | 119 | 0.6868 | 0.79 | 0.3443 | 1.4135 | 0.79 | 0.7528 | 0.1971 | 0.0748 |
| No log | 18.0 | 126 | 0.6290 | 0.795 | 0.3142 | 1.8030 | 0.795 | 0.7657 | 0.1476 | 0.0621 |
| No log | 19.0 | 133 | 0.6454 | 0.79 | 0.3213 | 1.6664 | 0.79 | 0.7785 | 0.1649 | 0.0645 |
| No log | 20.0 | 140 | 0.6089 | 0.785 | 0.3228 | 1.5436 | 0.785 | 0.7729 | 0.1708 | 0.0639 |
| No log | 21.0 | 147 | 0.6715 | 0.785 | 0.3289 | 1.3422 | 0.785 | 0.7598 | 0.1787 | 0.0768 |
| No log | 22.0 | 154 | 0.7075 | 0.79 | 0.3342 | 1.6069 | 0.79 | 0.7684 | 0.1587 | 0.0656 |
| No log | 23.0 | 161 | 0.6226 | 0.805 | 0.3067 | 1.2400 | 0.805 | 0.7881 | 0.1611 | 0.0716 |
| No log | 24.0 | 168 | 0.7501 | 0.77 | 0.3506 | 1.8952 | 0.7700 | 0.7530 | 0.1637 | 0.0746 |
| No log | 25.0 | 175 | 0.6039 | 0.775 | 0.3168 | 1.4196 | 0.775 | 0.7647 | 0.1701 | 0.0664 |
| No log | 26.0 | 182 | 0.6252 | 0.775 | 0.3260 | 1.4914 | 0.775 | 0.7507 | 0.1733 | 0.0657 |
| No log | 27.0 | 189 | 0.6590 | 0.79 | 0.3303 | 1.5970 | 0.79 | 0.7773 | 0.1695 | 0.0747 |
| No log | 28.0 | 196 | 0.5920 | 0.815 | 0.2988 | 1.6841 | 0.815 | 0.8127 | 0.1711 | 0.0635 |
| No log | 29.0 | 203 | 0.5982 | 0.785 | 0.3163 | 1.6290 | 0.785 | 0.7678 | 0.1641 | 0.0597 |
| No log | 30.0 | 210 | 0.5693 | 0.805 | 0.3028 | 1.4954 | 0.805 | 0.7917 | 0.1566 | 0.0578 |
| No log | 31.0 | 217 | 0.5860 | 0.805 | 0.2964 | 1.3856 | 0.805 | 0.7966 | 0.1413 | 0.0599 |
| No log | 32.0 | 224 | 0.5380 | 0.805 | 0.2775 | 1.6946 | 0.805 | 0.7981 | 0.1526 | 0.0494 |
| No log | 33.0 | 231 | 0.5041 | 0.8 | 0.2745 | 1.6025 | 0.8000 | 0.7887 | 0.1639 | 0.0498 |
| No log | 34.0 | 238 | 0.5134 | 0.83 | 0.2700 | 1.3768 | 0.83 | 0.8161 | 0.1464 | 0.0526 |
| No log | 35.0 | 245 | 0.5371 | 0.81 | 0.2820 | 1.3584 | 0.81 | 0.7982 | 0.1466 | 0.0552 |
| No log | 36.0 | 252 | 0.4987 | 0.815 | 0.2711 | 1.3735 | 0.815 | 0.8056 | 0.1540 | 0.0490 |
| No log | 37.0 | 259 | 0.5145 | 0.81 | 0.2814 | 1.3537 | 0.81 | 0.8000 | 0.1415 | 0.0521 |
| No log | 38.0 | 266 | 0.4992 | 0.815 | 0.2721 | 1.3420 | 0.815 | 0.7974 | 0.1453 | 0.0497 |
| No log | 39.0 | 273 | 0.4992 | 0.795 | 0.2748 | 1.3579 | 0.795 | 0.7757 | 0.1485 | 0.0502 |
| No log | 40.0 | 280 | 0.4881 | 0.82 | 0.2634 | 1.3745 | 0.82 | 0.8058 | 0.1504 | 0.0475 |
| No log | 41.0 | 287 | 0.4977 | 0.81 | 0.2750 | 1.3208 | 0.81 | 0.7965 | 0.1520 | 0.0504 |
| No log | 42.0 | 294 | 0.4865 | 0.815 | 0.2644 | 1.3840 | 0.815 | 0.8056 | 0.1517 | 0.0452 |
| No log | 43.0 | 301 | 0.5034 | 0.81 | 0.2722 | 1.3683 | 0.81 | 0.7967 | 0.1404 | 0.0514 |
| No log | 44.0 | 308 | 0.4925 | 0.815 | 0.2692 | 1.3979 | 0.815 | 0.8056 | 0.1386 | 0.0462 |
| No log | 45.0 | 315 | 0.4643 | 0.825 | 0.2608 | 1.3015 | 0.825 | 0.8148 | 0.1516 | 0.0442 |
| No log | 46.0 | 322 | 0.4851 | 0.82 | 0.2666 | 1.2561 | 0.82 | 0.8018 | 0.1494 | 0.0461 |
| No log | 47.0 | 329 | 0.4751 | 0.82 | 0.2615 | 1.3167 | 0.82 | 0.8120 | 0.1544 | 0.0457 |
| No log | 48.0 | 336 | 0.4666 | 0.82 | 0.2596 | 1.2470 | 0.82 | 0.8120 | 0.1326 | 0.0443 |
| No log | 49.0 | 343 | 0.4856 | 0.815 | 0.2659 | 1.3283 | 0.815 | 0.8081 | 0.1501 | 0.0474 |
| No log | 50.0 | 350 | 0.4690 | 0.83 | 0.2618 | 1.3227 | 0.83 | 0.8208 | 0.1448 | 0.0435 |
| No log | 51.0 | 357 | 0.4835 | 0.81 | 0.2670 | 1.2956 | 0.81 | 0.7961 | 0.1425 | 0.0471 |
| No log | 52.0 | 364 | 0.4857 | 0.82 | 0.2598 | 1.3115 | 0.82 | 0.8134 | 0.1547 | 0.0478 |
| No log | 53.0 | 371 | 0.4747 | 0.82 | 0.2654 | 1.3717 | 0.82 | 0.8026 | 0.1596 | 0.0453 |
| No log | 54.0 | 378 | 0.4925 | 0.815 | 0.2649 | 1.2289 | 0.815 | 0.8058 | 0.1452 | 0.0486 |
| No log | 55.0 | 385 | 0.4670 | 0.825 | 0.2611 | 1.3080 | 0.825 | 0.8102 | 0.1307 | 0.0434 |
| No log | 56.0 | 392 | 0.4878 | 0.81 | 0.2636 | 1.3040 | 0.81 | 0.7961 | 0.1546 | 0.0478 |
| No log | 57.0 | 399 | 0.4679 | 0.82 | 0.2600 | 1.2618 | 0.82 | 0.8038 | 0.1516 | 0.0430 |
| No log | 58.0 | 406 | 0.4802 | 0.815 | 0.2629 | 1.3054 | 0.815 | 0.8079 | 0.1448 | 0.0476 |
| No log | 59.0 | 413 | 0.4746 | 0.82 | 0.2615 | 1.3177 | 0.82 | 0.8064 | 0.1308 | 0.0457 |
| No log | 60.0 | 420 | 0.4784 | 0.82 | 0.2608 | 1.2495 | 0.82 | 0.8134 | 0.1336 | 0.0463 |
| No log | 61.0 | 427 | 0.4751 | 0.82 | 0.2630 | 1.2886 | 0.82 | 0.8086 | 0.1416 | 0.0459 |
| No log | 62.0 | 434 | 0.4751 | 0.815 | 0.2606 | 1.2453 | 0.815 | 0.8058 | 0.1529 | 0.0455 |
| No log | 63.0 | 441 | 0.4737 | 0.825 | 0.2629 | 1.2975 | 0.825 | 0.8113 | 0.1286 | 0.0451 |
| No log | 64.0 | 448 | 0.4840 | 0.815 | 0.2631 | 1.3210 | 0.815 | 0.8036 | 0.1392 | 0.0472 |
| No log | 65.0 | 455 | 0.4747 | 0.82 | 0.2615 | 1.3054 | 0.82 | 0.8086 | 0.1491 | 0.0456 |
| No log | 66.0 | 462 | 0.4767 | 0.815 | 0.2618 | 1.3056 | 0.815 | 0.8058 | 0.1517 | 0.0459 |
| No log | 67.0 | 469 | 0.4748 | 0.82 | 0.2615 | 1.3046 | 0.82 | 0.8086 | 0.1525 | 0.0453 |
| No log | 68.0 | 476 | 0.4782 | 0.815 | 0.2626 | 1.3088 | 0.815 | 0.8058 | 0.1519 | 0.0461 |
| No log | 69.0 | 483 | 0.4769 | 0.815 | 0.2616 | 1.3133 | 0.815 | 0.8058 | 0.1555 | 0.0456 |
| No log | 70.0 | 490 | 0.4767 | 0.815 | 0.2622 | 1.3067 | 0.815 | 0.8058 | 0.1435 | 0.0457 |
| No log | 71.0 | 497 | 0.4776 | 0.815 | 0.2623 | 1.3111 | 0.815 | 0.8058 | 0.1533 | 0.0458 |
| 0.1688 | 72.0 | 504 | 0.4770 | 0.815 | 0.2621 | 1.3078 | 0.815 | 0.8058 | 0.1605 | 0.0457 |
| 0.1688 | 73.0 | 511 | 0.4783 | 0.815 | 0.2625 | 1.3109 | 0.815 | 0.8058 | 0.1503 | 0.0458 |
| 0.1688 | 74.0 | 518 | 0.4776 | 0.815 | 0.2621 | 1.3117 | 0.815 | 0.8058 | 0.1648 | 0.0458 |
| 0.1688 | 75.0 | 525 | 0.4784 | 0.815 | 0.2627 | 1.3110 | 0.815 | 0.8058 | 0.1463 | 0.0458 |
| 0.1688 | 76.0 | 532 | 0.4779 | 0.815 | 0.2625 | 1.3125 | 0.815 | 0.8058 | 0.1577 | 0.0457 |
| 0.1688 | 77.0 | 539 | 0.4794 | 0.815 | 0.2628 | 1.3110 | 0.815 | 0.8058 | 0.1420 | 0.0459 |
| 0.1688 | 78.0 | 546 | 0.4776 | 0.815 | 0.2623 | 1.3120 | 0.815 | 0.8058 | 0.1517 | 0.0455 |
| 0.1688 | 79.0 | 553 | 0.4789 | 0.815 | 0.2627 | 1.3101 | 0.815 | 0.8058 | 0.1460 | 0.0459 |
| 0.1688 | 80.0 | 560 | 0.4784 | 0.815 | 0.2626 | 1.3127 | 0.815 | 0.8058 | 0.1518 | 0.0457 |
| 0.1688 | 81.0 | 567 | 0.4782 | 0.815 | 0.2625 | 1.3103 | 0.815 | 0.8058 | 0.1408 | 0.0457 |
| 0.1688 | 82.0 | 574 | 0.4791 | 0.815 | 0.2627 | 1.3166 | 0.815 | 0.8058 | 0.1586 | 0.0458 |
| 0.1688 | 83.0 | 581 | 0.4785 | 0.815 | 0.2625 | 1.3116 | 0.815 | 0.8058 | 0.1436 | 0.0459 |
| 0.1688 | 84.0 | 588 | 0.4783 | 0.815 | 0.2624 | 1.3113 | 0.815 | 0.8058 | 0.1476 | 0.0458 |
| 0.1688 | 85.0 | 595 | 0.4785 | 0.815 | 0.2625 | 1.3169 | 0.815 | 0.8058 | 0.1500 | 0.0457 |
| 0.1688 | 86.0 | 602 | 0.4782 | 0.815 | 0.2625 | 1.3127 | 0.815 | 0.8058 | 0.1496 | 0.0457 |
| 0.1688 | 87.0 | 609 | 0.4778 | 0.815 | 0.2623 | 1.3119 | 0.815 | 0.8058 | 0.1496 | 0.0456 |
| 0.1688 | 88.0 | 616 | 0.4783 | 0.815 | 0.2625 | 1.3118 | 0.815 | 0.8058 | 0.1529 | 0.0458 |
| 0.1688 | 89.0 | 623 | 0.4784 | 0.815 | 0.2625 | 1.3149 | 0.815 | 0.8058 | 0.1485 | 0.0457 |
| 0.1688 | 90.0 | 630 | 0.4781 | 0.815 | 0.2624 | 1.3137 | 0.815 | 0.8058 | 0.1472 | 0.0457 |
| 0.1688 | 91.0 | 637 | 0.4784 | 0.815 | 0.2626 | 1.3111 | 0.815 | 0.8058 | 0.1492 | 0.0458 |
| 0.1688 | 92.0 | 644 | 0.4785 | 0.815 | 0.2625 | 1.3177 | 0.815 | 0.8058 | 0.1485 | 0.0457 |
| 0.1688 | 93.0 | 651 | 0.4790 | 0.815 | 0.2626 | 1.3208 | 0.815 | 0.8058 | 0.1462 | 0.0457 |
| 0.1688 | 94.0 | 658 | 0.4788 | 0.815 | 0.2625 | 1.3178 | 0.815 | 0.8058 | 0.1396 | 0.0458 |
| 0.1688 | 95.0 | 665 | 0.4785 | 0.815 | 0.2625 | 1.3203 | 0.815 | 0.8058 | 0.1484 | 0.0457 |
| 0.1688 | 96.0 | 672 | 0.4786 | 0.815 | 0.2625 | 1.3168 | 0.815 | 0.8058 | 0.1470 | 0.0457 |
| 0.1688 | 97.0 | 679 | 0.4786 | 0.815 | 0.2625 | 1.3167 | 0.815 | 0.8058 | 0.1470 | 0.0457 |
| 0.1688 | 98.0 | 686 | 0.4787 | 0.815 | 0.2625 | 1.3192 | 0.815 | 0.8058 | 0.1408 | 0.0457 |
| 0.1688 | 99.0 | 693 | 0.4787 | 0.815 | 0.2625 | 1.3205 | 0.815 | 0.8058 | 0.1408 | 0.0457 |
| 0.1688 | 100.0 | 700 | 0.4787 | 0.815 | 0.2625 | 1.3204 | 0.815 | 0.8058 | 0.1408 | 0.0457 |
### 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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