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library_name: transformers
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---
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# Model Card for Model ID
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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---
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library_name: transformers
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license: mit
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language:
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- de
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pipeline_tag: text-classification
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---
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# Model Card for Model ID
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Fine-tuned (XLM-R Large)[https://huggingface.co/FacebookAI/xlm-roberta-large] for task of classifying sentences as factual or not. The taxonomy for factual claims follows Wilms et al. 2021. The model was first trained on a Telegram dataset that was annotated using GPT-4o with this (prompt)[https://huggingface.co/Sami92/XLM-R-Large-ClaimDetection/blob/main/FactualityPrompt_GPT.txt]. In a second step it was trained on the data from Risch et al. 2021. It was tested on a sample of Telegram posts that were annotated by four trained coders.
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## More Information [optional]
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@misc{wilms_annotation_2021,
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title = {Annotation {Guidelines} for {GermEval} 2021 {Shared} {Task} on the {Identification} of {Toxic}, {Engaging}, and {Fact}-{Claiming} {Comments}. {Excerpt} of an unpublished codebook of the {DEDIS} research group at {Heinrich}-{Heine}-{University} {Düsseldorf} (full version available on request)},
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author = {Wilms, L. and Heinbach, D. and Ziegele, M.},
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year = {2021},
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}
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@inproceedings{risch_overview_2021,
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address = {Duesseldorf, Germany},
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title = {Overview of the {GermEval} 2021 {Shared} {Task} on the {Identification} of {Toxic}, {Engaging}, and {Fact}-{Claiming} {Comments}},
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url = {https://aclanthology.org/2021.germeval-1.1},
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booktitle = {Proceedings of the {GermEval} 2021 {Shared} {Task} on the {Identification} of {Toxic}, {Engaging}, and {Fact}-{Claiming} {Comments}},
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publisher = {Association for Computational Linguistics},
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author = {Risch, Julian and Stoll, Anke and Wilms, Lena and Wiegand, Michael},
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year = {2021},
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}
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