| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - food101 |
| metrics: |
| - accuracy |
| model-index: |
| - name: image_classification |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: food101 |
| type: food101 |
| config: default |
| split: train[:5000] |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.911 |
| --- |
| |
| <!-- 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. --> |
|
|
| # image_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 food101 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5938 |
| - Accuracy: 0.911 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 2.7307 | 0.99 | 62 | 2.5306 | 0.833 | |
| | 1.8698 | 2.0 | 125 | 1.7637 | 0.903 | |
| | 1.5629 | 2.98 | 186 | 1.5856 | 0.915 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.33.1 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
| |
