Maxime Gohier · PyLaia · Published November 12, 2022

New France (17th-18th Century)

Text Recognition

Description

Model developped by the partnership project Nouvelle-France numérique (Digital New France), from the Université du Québec à Rimouski, Bibliothèque et Archives nationales du Québec, Université de Montréal, Bibliothèque et Archives Canada, Musée de la Civilisation, Archives nationales d'Outre-Mer. Based principally on secretary's writting, includes documents from Series C11A, C13A and F3 (ANOM), Melzac Collection (UdeM), and Ordonnanes d'intendants (BAnQ).

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Very low error rate5% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 5% 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.

Words304,325
Lines41,646
Training Pages1,639
Model ID46116
Centuries
17th c.18th c.