NIOD_WarLet_1935-1950

Free Public AI Model for Handwritten Text Recognition with Transkribus

NIOD_WarLet_1935-1950

The HTR model ‘NIOD_WarLet_1935-1950’ was trained on handwritten correspondence in Dutch, originating from the period 1935-1950.

The training set consists of 1087 ‘Ground Truth’ transcriptions of high-resolution scans.
All documents included are part of the archival collection known as ‘247 Correspondentie’ held by the NIOD Institute for War, Holocaust, and Genocide Studies in Amsterdam.
The training set contains personal correspondence from a wide variety of letter writers (e.g., children, soldiers, Jewish people in hiding).

This model was created as part of the project ‘First-Hand Accounts of War: War letters (1935-1950) from NIOD digitised’, that ran from 2020 till 2023.

All documents used for training and validation were scanned and transcribed within this project.
This project was funded by the Mondriaan Fund, the Dutch Ministry of Health, Welfare, and Sport, and the NIOD Institute for War, Holocaust, and Genocide Studies in Amsterdam.

The ‘Ground Truth’ training set is created by project members Annelies van Nispen, Carlijn Keijzer and Milan van Lange. Additional transcription and correction of ‘Ground Truth’ transcriptions was performed under supervision of Muriël Bouman by citizen scientists Hillebrand Verkroost, Bart Cohen, Evelien Bachrach, Marjo Janssens, and Cocky Sietses.

The validation set contains a sample of 17 ‘Ground Truth’ transcriptions from various writers and sub-collections.

The model is trained using the PyLaia HTR engine, 250 epochs were trained with a learning rate of 0.0003.
The HTR-model ‘IJsberg_PyLaia’ (id: 38769) was used as a basemodel.

Model Overview

Name:
NIOD_WarLet_1935-1950
Creator:
NIOD Institute for War, Holocaust, and Genocide Studies
Model ID:
53102
Century:
20th
Languages:
Dutch, Flemish
Script:
Latin alphabet
Engine:
PyLaia
Material:
Handwritten
CER on validation set:
4.60 %
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This AI model was trained to automatically convert text from images of historical Latin alphabet documents into editable and searchable text.