Hugging Face's logo language: ar de en es fr it lv nl pt zh multilingual bert base multilingual cased ner hrl Model description bert base multilingual cased ner hrl is a Named Entity Recognition model for 10 high resourced languages (Arabic, German, English, Spanish, French, Italian, Latvian, Dutch, Portuguese and Chinese) based on a fine tuned mBERT base model. It has been trained to recognize three types of entities: location (LOC), organizations (ORG), and person (PER). Specifically, this model is a bert base multilingual cased model that was fine tuned on an aggregation of 10 high resourced languages Intended uses & limitations How to use You can use this model with Transformers pipeline for NER. Limitations and bias This model is limited by its training dataset of entity annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains. Training data The training data for the 10 languages are from: Language Dataset Arabic ANERcorp German conll 2003 English conll 2003 Spanish conll 2002 French Europeana Newspapers Italian Italian I CAB Latvian Latvian NER Dutch conll 2002 Portuguese Paramopama + Second Harem Chinese MSRA T…
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