Transkribus Community · PyLaia · Published October 16, 2021

Transkribus English Handwriting M3

Text Recognition

Description

Based on Transkribus English Handwriting M2 (Bentham writing and also including a number of collections from 18th to 20th C.). Curated by the Transkribus team, this model is occasionally updated with community data for continuous improvement.

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Transkribus English Handwriting M3
Use this modelOpen in Transkribus
Low error rate5.1% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 5.1% 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.

Words2,125,253
Lines325,503
Training Pages11,559
Model ID37646
Languages
English
Centuries
18th c.19th c.20th c.