pagantibet · PyLaia · Published October 11, 2024

PaganTibet Ume 2

Text Recognition

Description

PaganTibet Ume 2 was developed as part of the PaganTibet project (pagantibet.com) at EPHE-PSL Paris, with funding from the European Union (ERC, Reconstructing the Pagan Religion of Tibet (2023-2028), 101097364). The model was trained on a dataset of 620 images from a diverse collection of Tibetan-language manuscripts, with 567 images used for training and 53 for validation. Most images consist of photographs of two manuscript pages.

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Low error rate5.56% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 5.56% 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.

Words15,659
Lines3,952
Training Pages567
Model ID193821
Languages
Tibetan