---
language:
- en
base_model:
- google-bert/bert-base-uncased
---
<!-- # Model Card for Model ID

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This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

## Model Details

### Model Description

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- **Finetuned from model :** google-bert/bert-base-uncased

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
This model classifies food recipe or ingredient into three disctinct categories: Vegan, Vegetarian and Non-vegetarian

## Bias, Risks, and Limitations

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This model is trained on controlled dataset.

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### Recommendations

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Model should be fine-tuned on huge book corpus and large synthetic dataset.
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## How to Get Started with the Model

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1. Download model.
2. Run testing script.

## Training Details

### Training Data

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1. https://huggingface.co/datasets/rajputnavya/food-classification-mlm-clean
2. https://huggingface.co/datasets/rajputnavya/food-classification-nsp-format
3. https://huggingface.co/datasets/rajputnavya/food-classification-recipe-classification-data/blob/main/fine_tune_format.jsonl
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### Training Procedure

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1. Training on mlm and nsp dataset combined
2. Fine-tuning on synthetic dataset for recipe classification

### Results

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{'accuracy': 0.9166666666666666, 'precision': 0.9333333333333332, 'recall': 0.9166666666666666, 'f1_score': 0.9153439153439153}