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