guido.russo · PyLaia · Published January 13, 2026
Unina MAGIC Platea 1.0
Text Recognition
Description
It has been trained by the University of Naples Federico II, "Ettore Pancini" Physics Department, MAGIC Project.
The model is trained on the Platea 3558 "Archivio di Stato di Caserta".
Archival Unit: Platea dei fondi, beni e rendite che costituiscono l’amministrazione del Real Sito di Caserta formata per ordine di S.M. Francesco I Re del Regno delle Due Sicilie dall’amministratore Cav. Sancio. Vol. I, Stato di Caserta
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Very low error rate2.1% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 2.1% 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.
Words64,954
Lines7,663
Training Pages243
Model ID469745