Beyond 2022 project · PyLaia · Published November 28, 2022

B2022 English Model M4

Text Recognition

Description

English with some Latin characters. By the Beyond 2022 project, Trinity College Dublin. Early 17th to late 19th century, 40 hands using Transkribus base model and 750,000 word ground truth. The model is particularly effective on secretary and copperplate texts and can be used as a base model for more cursive scripts.

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Use this modelOpen in Transkribus
Very low error rate3.5% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 3.5% 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.

Words759,625
Lines102,881
Training Pages2,934
Model ID48327
Centuries
17th c.18th c.19th c.