| --- |
| language: |
| - en |
| base_model: |
| - google-bert/bert-base-uncased |
| --- |
| <!-- # Model Card for Model ID |
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| <!-- Provide a quick summary of what the model is/does. --> |
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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). |
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| ## Model Details |
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| ### Model Description |
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| <!-- Provide a longer summary of what this model is. --> |
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| <!-- - **Developed by:** [More Information Needed] |
| - **Funded by [optional]:** [More Information Needed] |
| - **Shared by [optional]:** [More Information Needed] |
| - **Model type:** [More Information Needed] |
| - **Language(s) (NLP):** [More Information Needed] |
| - **License:** [More Information Needed] --> |
| - **Finetuned from model :** google-bert/bert-base-uncased |
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| ## Uses |
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| <!-- 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 |
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| ## Bias, Risks, and Limitations |
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| <!-- This section is meant to convey both technical and sociotechnical limitations. --> |
| This model is trained on controlled dataset. |
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| <!-- [More Information Needed] --> |
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| ### Recommendations |
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| <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
| Model should be fine-tuned on huge book corpus and large synthetic dataset. |
| <!-- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. --> |
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| ## How to Get Started with the Model |
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| <!-- Use the code below to get started with the model. --> |
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| 1. Download model. |
| 2. Run testing script. |
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| ## Training Details |
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| ### Training Data |
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| <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
| 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 |
| <!-- [More Information Needed] --> |
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| ### Training Procedure |
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| <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
| 1. Training on mlm and nsp dataset combined |
| 2. Fine-tuning on synthetic dataset for recipe classification |
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| ### Results |
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| <!-- [More Information Needed] --> |
| {'accuracy': 0.9166666666666666, 'precision': 0.9333333333333332, 'recall': 0.9166666666666666, 'f1_score': 0.9153439153439153} |
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