sinai.rusinek · PyLaia · Published November 10, 2022

DiJeSt 2.0

Text Recognition

Description

Retraining with pylaia of the model "Dijest for Hebrew script languages". Trained on a mix of historic Hebrew scripts and languages, in the framework of the project DiJeSt. For details: http://dijest.net/gtmodel

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Very low error rate2% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 2% 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.

Words773,726
Lines79,542
Training Pages1,757
Model ID46003
Languages
HebrewJudeo-ArabicLadinoYiddish