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chefkoch24/weak-ingredient-recognition-bert-base-cased-german
weak-ingredient-recognition-bert-base-cased-german is a token classification model from chefkoch24. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as openrail.
Weakly supervised token classification model for German recipe texts based on bert-base-german-cased.
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From the Hugging Face model README
Weakly supervised token classification model for German recipe texts based on bert-base-german-cased.
Code available: https://github.com/chefkoch24/weak-ingredient-recognition
Dataset: https://www.kaggle.com/datasets/sterby/german-recipes-dataset
Recognizes the following entities:<br> 'O': 0, <br> 'B-INGREDIENT': 1,<br> 'I-INGREDIENT': 2,<br> 'B-UNIT': 3,<br> 'I-UNIT': 4,<br> 'B-QUANTITY': 5,<br> 'I-QUANTITY': 6<br>
Training: <br> epochs: 2<br> optimizer: Adam<br> learning rate: 2e-5<br> max length: 512<br> batch size: 8<br> recipes: 7801<br>
The model was trained on single Geforce RTX2080 with 11GB GPU
Metrics on test set (weakly supervised): <br> accuracy_token 0.9965656995773315<br> f1_token 0.9965656995773315<br> precision_token 0.9965656995773315<br> recall_token 0.9965656995773315<br>