p.van.den.heuvel · PyLaia · Published March 12, 2025

Middeleeuws Amsterdam

Text Recognition

Description

Data van Stadsarchief Amsterdam i.s.m. Stichting Middeleeuwse Archieven Amsterdam, Johan Visser, Geertrui van Synghel, Jesse Dijkshoorn. Basemodel: Medieval_Scripts_M2.4

Try this model

Use this modelOpen in Transkribus
Low error rate5.11% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 5.11% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material. This is a larger model trained on diverse material, which generally makes it more robust across different handwriting styles. That said, larger training sets also make it harder to push the CER down further.

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.

Words1,562,527
Lines214,178
Training Pages4,700
Model ID305713
Languages
Dutch
Centuries
14th c.15th c.16th c.