| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - indoor-scene-classification |
| metrics: |
| - accuracy |
| model-index: |
| - name: scene_classification |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: indoor-scene-classification |
| type: indoor-scene-classification |
| config: full |
| split: test |
| args: full |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8491655969191271 |
| --- |
| |
| <!-- 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. --> |
|
|
| # scene_classification |
| |
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the indoor-scene-classification dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6106 |
| - Accuracy: 0.8492 |
| |
| ## 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: 3e-05 |
| - 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 |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 3.3172 | 1.0 | 341 | 2.8572 | 0.5109 | |
| | 2.2254 | 2.0 | 682 | 2.1453 | 0.6329 | |
| | 1.6202 | 3.0 | 1023 | 1.6283 | 0.7336 | |
| | 1.2313 | 4.0 | 1364 | 1.3402 | 0.7599 | |
| | 0.9576 | 5.0 | 1705 | 1.1237 | 0.8010 | |
| | 0.7654 | 6.0 | 2046 | 1.0270 | 0.8023 | |
| | 0.6416 | 7.0 | 2387 | 0.8848 | 0.8171 | |
| | 0.5353 | 8.0 | 2728 | 0.8381 | 0.8087 | |
| | 0.4516 | 9.0 | 3069 | 0.7570 | 0.8254 | |
| | 0.3925 | 10.0 | 3410 | 0.6667 | 0.8524 | |
| | 0.3453 | 11.0 | 3751 | 0.7583 | 0.8164 | |
| | 0.2944 | 12.0 | 4092 | 0.6783 | 0.8350 | |
| | 0.294 | 13.0 | 4433 | 0.7128 | 0.8312 | |
| | 0.2507 | 14.0 | 4774 | 0.6632 | 0.8331 | |
| | 0.2355 | 15.0 | 5115 | 0.6730 | 0.8421 | |
| | 0.2267 | 16.0 | 5456 | 0.6572 | 0.8357 | |
| | 0.2032 | 17.0 | 5797 | 0.7058 | 0.8280 | |
| | 0.1908 | 18.0 | 6138 | 0.6374 | 0.8485 | |
| | 0.1857 | 19.0 | 6479 | 0.6831 | 0.8312 | |
| | 0.1727 | 20.0 | 6820 | 0.6961 | 0.8254 | |
| | 0.1692 | 21.0 | 7161 | 0.6306 | 0.8402 | |
| | 0.1642 | 22.0 | 7502 | 0.6291 | 0.8485 | |
| | 0.1618 | 23.0 | 7843 | 0.6058 | 0.8582 | |
| | 0.1593 | 24.0 | 8184 | 0.6780 | 0.8389 | |
| | 0.1399 | 25.0 | 8525 | 0.6330 | 0.8485 | |
| | 0.1373 | 26.0 | 8866 | 0.6550 | 0.8408 | |
| | 0.1334 | 27.0 | 9207 | 0.6857 | 0.8421 | |
| | 0.1388 | 28.0 | 9548 | 0.6338 | 0.8415 | |
| | 0.1423 | 29.0 | 9889 | 0.6272 | 0.8517 | |
| | 0.1288 | 30.0 | 10230 | 0.6409 | 0.8556 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.33.3 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
| |
