University College London – Bentham project · CITlab · Published April 7, 2016
English Writing M1
Text Recognition
Description
Based on Jeremy Bentham and secretaries from early 19th century. 50.000+ words.
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Very low error rate3.66% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 3.66% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material. This is a smaller, specialised model. It may achieve a very low CER on material similar to its training data, but could be less robust on unfamiliar handwriting or layouts.
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.
Model ID133