Transkribus · Super Model · Published March 19, 2025
Dansk Dokumentalist (Super Model)
Description
Dansk Dokumentalist is a highly capable Transkribus Super Model for recognising handwritten and printed Danish texts. Trained on an extensive Danish-language dataset enriched with community contributions, it is designed to handle a wide variety of documents, from medieval manuscripts to modern printed works. The model excels across different styles and periods of Danish writing, offering reliable performance for historical research, archival work, and contemporary projects alike. Super Models are generalists and usually provide great out-of-the-box performance on a wide variety of materials. Users can then leverage the processing output of the Super Model for correcting and using it as training material for dedicated specialist models.
Special thanks to Johan Heinsen from Aalborg University for coordinating a large part of community contributions, from Emilie Luther Valentin, Nina Koefoed, Line Keller Ottosen, Tine Reeh, Nanna Eva Nissen, Kamilla Matthiassen and Louise Karoline Sort.
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Very low error rate3.7% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 3.7% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material. Super Models are trained on very large and diverse datasets, making them robust across a wide range of handwriting styles and languages. Because of this diversity, a low CER on the validation set is a strong indicator of general-purpose quality.
Measured on the model's own validation data. Results on your documents may differ depending on handwriting style, document condition, language, and how closely your material resembles the training data.
Words12,849,906
Model ID309713