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--- |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- depression |
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- roberta |
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base_model: rafalposwiata/deproberta-large-v1 |
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--- |
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Fine-tuned [DepRoBERTa](https://huggingface.co/rafalposwiata/deproberta-large-v1) model for detecting the level of depression as **not depression**, **moderate** or **severe**, based on social media posts in English. |
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Model was part of the winning solution for [the Shared Task on Detecting Signs of Depression |
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from Social Media Text](https://competitions.codalab.org/competitions/36410) at [LT-EDI-ACL2022](https://sites.google.com/view/lt-edi-2022/home). |
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More information can be found in the following paper: [OPI@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text using RoBERTa Pre-trained Language Models](https://aclanthology.org/2022.ltedi-1.40/). |
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If you use this model, please cite: |
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``` |
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@inproceedings{poswiata-perelkiewicz-2022-opi, |
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title = "{OPI}@{LT}-{EDI}-{ACL}2022: Detecting Signs of Depression from Social Media Text using {R}o{BERT}a Pre-trained Language Models", |
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author = "Po{\'s}wiata, Rafa{\l} and Pere{\l}kiewicz, Micha{\l}", |
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booktitle = "Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion", |
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month = may, |
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year = "2022", |
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address = "Dublin, Ireland", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.ltedi-1.40", |
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doi = "10.18653/v1/2022.ltedi-1.40", |
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pages = "276--282", |
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} |
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``` |
