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--- |
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license: mit |
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library_name: spacy |
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tags: |
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- food |
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--- |
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# Food NER |
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Github Repo: <a href=https://github.com/randymi01/food_ner> https://github.com/randymi01/food_ner</a> |
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Spacy Food Name Entity Recognition (NER) model trained on StanfordNLP CRF recipe dataset |
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## Installation |
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Use the package manager [pip](https://pip.pypa.io/en/stable/) to install spacy version spacy==3.5.0 and then download the spacy en_core_web_sm model. |
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```bash |
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pip install spacy==3.5.0 |
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python -m spacy download en_core_web_sm |
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``` |
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## Usage |
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```python |
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import spacy |
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nlp = spacy.load("model") |
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# returns (spring mix, chicken breast, chili, hamburger meat) |
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nlp("I have spring mix, chicken breast, chili, and hamburger meat").ents |
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``` |
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## Model Hyperparameters |
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* Epochs: 10 |
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* Batch Size: 4-32 |
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* Optimizer: Adam |
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* lr = 5e-03 |
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* drop_rate = 0.5 |
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## Model Performance |
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![alt text](https://github.com/randymi01/food_ner/blob/main/training_loss.png?raw=true) |
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![alt text](https://github.com/randymi01/food_ner/blob/main/validation_loss.png?raw=true) |
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## License |
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[MIT](https://choosealicense.com/licenses/mit/) |