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jonathan.hauller · PyLaia · Published July 20, 2026

Ratsmanuale_1798-1552_M14

Text Recognition

Description

Language: deu - German Base Model: The German Giant I Perform binarization: no Use existing line polygons for training: yes Omit lines by tag: unclear Train Abbrevs: no Train Tags: no Train Set: Train Set M13 + GT B II 185, 173, 172, 157, 153, 152, 150, 140 Validation Set: Validation Set M13 + GT B II 151

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Very low error rate4.79% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 4.79% 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.

Words286,717
Lines65,844
Training Pages723
Model ID605869
Languages
German