| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| base_model: google/vit-base-patch16-224-in21k |
| model-index: |
| - name: snacks_classification |
| results: [] |
| datasets: |
| - Matthijs/snacks |
| --- |
| |
| <!-- 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. --> |
|
|
| # snacks_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 an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4458 |
| - Accuracy: 0.8942 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 13 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 303 | 0.7200 | 0.8649 | |
| | 1.0168 | 2.0 | 606 | 0.5468 | 0.8723 | |
| | 1.0168 | 3.0 | 909 | 0.4612 | 0.8848 | |
| | 0.3765 | 4.0 | 1212 | 0.5239 | 0.8660 | |
| | 0.2585 | 5.0 | 1515 | 0.4193 | 0.8890 | |
| | 0.2585 | 6.0 | 1818 | 0.4571 | 0.8775 | |
| | 0.2038 | 7.0 | 2121 | 0.4538 | 0.8838 | |
| | 0.2038 | 8.0 | 2424 | 0.4508 | 0.8880 | |
| | 0.1827 | 9.0 | 2727 | 0.4748 | 0.8880 | |
| | 0.1568 | 10.0 | 3030 | 0.4928 | 0.8764 | |
| | 0.1568 | 11.0 | 3333 | 0.3684 | 0.9099 | |
| | 0.1305 | 12.0 | 3636 | 0.4205 | 0.8984 | |
| | 0.1305 | 13.0 | 3939 | 0.4537 | 0.8963 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.2 |
