habib.ibrahim · PyLaia · Published March 4, 2025
Agapet13
Text Recognition
Description
As part of the Agapet project, which aims to train with Transkribus HTR models to digitize Christian Arabic literature from the 9th to the 19th century, we present a new model, Agapet13, for the manuscripts of the 13th century. This development follows the training of Agapet17 for the manuscripts of the 17th century.
https://www.transkribus.org/model/agapet17-christian-arabic-manuscripts
This model was trained on the script of 13th-century copyist Poimen al-Siqi. The primary source for the dataset was the Sinai Ar. 418. Following its dissemination, the script has been widely circulated in both Damascus and Sinai.
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Low error rate7.48% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 7.48% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material.
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.
Words59,103
Lines6,395
Training Pages307
Model ID300833