Amsterdam City Archives · PyLaia · Published March 11, 2022

Notarial 17th Century Super Model_v2

Text Recognition

Description

Consisting of 18 different notarial handwritings from the 17th Century (every handwriting consists of 73-3207 scans training material). In total 11.783 scans training material and 375 scans validation material. Notaries included: Bruijningh, Mathijsz, Schaef, De Winter, Westfrisius, Van der Groe, A. van de Ven, Van Sevenhoven, Des Pommare, Borsselaer, Pondt, De Vos, J. van de Ven, Venkel, Stafmaeker Varlet, Van Breugel, Lock and Doornick. Collection: Amsterdam City Archives.

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Very low error rate4.8% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 4.8% 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.

Words3,933,340
Lines899,765
Training Pages11,783
Model ID40382
Languages
Dutch
Centuries
17th c.