Transkribus Team · PyLaia · Published November 30, 2021

Transkribus Italian Handwriting M1

Text Recognition

Description

Italian handwriting, 16th-19th century. This is a generic model trained on a diverse dataset. Such models provide good results without the need for any extra training work. However, the best results can usually be achieved by training a special model for homogenous material, e. g. texts written by the same person or from a narrow historical period. Curated by the Transkribus team, this model is occasionally updated with community data for continuous improvement.

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Low error rate6.7% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 6.7% 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.

Words653,630
Lines277,202
Training Pages4,652
Model ID38440
Languages
Italian