Dataset Open Access

Temporal Model XLM-RoBERTa-Large_TempEval-3

Kirsanov Simon

Temporal Model "XLM-RoBERTa-Large" finetuned on the "TempEval-3" dataset to solve the tasks of extraction and classification of temporal entities. Model produced in the master's thesis "Extraction and Classification of Time in Unstructured Data [Kirsanov, 2023]".

Files (1.7 GB)
Name Size
xlm-roberta-large_tempeval_multi.zip
md5:cb22f093746e08933eb34163ed943b33 		1.7 GB Download
Publication date:
November 1, 2023
DOI:
10.25592/uhhfdm.13589

DOI Badge

Markdown 

[![DOI](https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13589.svg)](https://doi.org/10.25592/uhhfdm.13589)

reStructedText 

.. image:: https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13589.svg
   :target: https://doi.org/10.25592/uhhfdm.13589

HTML 

<a href="https://doi.org/10.25592/uhhfdm.13589"><img src="https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13589.svg" alt="DOI"></a>

Image URL 

https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13589.svg

Target URL 

https://doi.org/10.25592/uhhfdm.13589

Keyword(s):
xlm-roberta temporal tagging temporal extraction information extraction natural language processing nlp named entity recognition ner timex3 tempeval timebank aquaint
Communities:
License (for files):
Creative Commons Attribution 4.0 International

Versions

Version 1 10.25592/uhhfdm.13589 Nov 1, 2023
Cite all versions? You can cite all versions by using the DOI 10.25592/uhhfdm.13588. This DOI represents all versions, and will always resolve to the latest one.

Cite record as

Export