Scandi NER Model 🏔️ A multilingual Named Entity Recognition model trained on multiple Scandi language datasets plus English and German. The model identifies Person (PER) , Organization (ORG) , and Location (LOC) entities. Model Description This model is based on MediaCatch/mmBERT base scandi ner and has been fine tuned for token classification on a combined dataset of Scandi NER corpora. It supports: 🇩🇰 Danish Multiple high quality datasets including DaNE 🇸🇪 Swedish SUC 3.0, Swedish NER corpus, and more 🇳🇴 Norwegian NorNE (Bokmål and Nynorsk) 🇬🇧 English CoNLL 2003 and additional datasets Performance The model achieves the following performance on the held out test set: Metric Score F1 Score 0.8330 Precision 0.8455 Recall 0.8208 Quick Start Supported Entity Types The model predicts the following entity types using BIO tagging: PER (Person): Names of people ORG (Organization): Companies, institutions, organizations LOC (Location): Geographic locations, places Training Data The model was trained on a combination of the following datasets: eriktks/conll2003 : 20,682 examples NbAiLab/norne bokmaal 7 : 20,044 examples NbAiLab/norne nynorsk 7 : 17,575 examples KBLab/sucx3 ner ori…
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