eric.werner.mail · PyLaia · Published September 18, 2024

Early Tibetan Manuscript Uchan

Text Recognition

Description

A HTR model based on old Tibetan dbu-can manuscripts.

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Very low error rate1.9% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 1.9% 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.

Words199,979
Lines6,671
Training Pages503
Model ID176765
Languages
Tibetan
Centuries
12th c.13th c.14th c.