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Mini-dataset for VL-Models fine-tuning (VL-Tune-dataset-mini)

Hussein Mohammed

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  <dc:creator>Hussein Mohammed</dc:creator>
  <dc:date>2023-06-30</dc:date>
  <dc:description>A minimal dataset of 125 image-text pairs and 10 text queries for fine-tuning vision-language models on manuscript images. It is dedicated to the task of text-based image retrieval, and splited into "train" and "test" sets. The train set consists of 100 image-text pairs, while the test set consists of 25 image-text pairs. This dataset is constructed from the following sources:

- images from the DocExplore dataset of medieval manuscripts.

- images from two manuscripts from Al-Ḥarīrī, Maqāmāt, © Paris, Bibliothèque nationale de France. Département des manuscrits, namely MS arabe 3929 and MS arabe 5847.

- the descriptions in the text files are prepared by Martina Dinelli

The research for this work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2176 ‘Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures', project no. 390893796. The research was conducted within the scope of the Centre for the Study of Manuscript Cultures (CSMC) at Universität Hamburg.</dc:description>
  <dc:identifier>https://www.fdr.uni-hamburg.de/record/12671</dc:identifier>
  <dc:identifier>10.25592/uhhfdm.12671</dc:identifier>
  <dc:identifier>oai:fdr.uni-hamburg.de:12671</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>doi:10.25592/uhhfdm.12670</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Vision-Language Models, Dataset</dc:subject>
  <dc:title>Mini-dataset for VL-Models fine-tuning (VL-Tune-dataset-mini)</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
Publication date:
June 30, 2023
DOI:
10.25592/uhhfdm.12671

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Keyword(s):
Vision-Language Models, Dataset
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Version 1.0 10.25592/uhhfdm.12671 Jun 30, 2023
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