|
--- |
|
language: |
|
- en |
|
library_name: transformers |
|
tags: |
|
- depression |
|
- roberta |
|
--- |
|
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. |
|
|
|
Model was part of the winning solution for [the Shared Task on Detecting Signs of Depression |
|
from Social Media Text](https://competitions.codalab.org/competitions/36410) at [LT-EDI-ACL2022](https://sites.google.com/view/lt-edi-2022/home). |
|
|
|
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/). |
|
|
|
If you use this model, please cite: |
|
|
|
``` |
|
@inproceedings{poswiata-perelkiewicz-2022-opi, |
|
title = "{OPI}@{LT}-{EDI}-{ACL}2022: Detecting Signs of Depression from Social Media Text using {R}o{BERT}a Pre-trained Language Models", |
|
author = "Po{\'s}wiata, Rafa{\l} and Pere{\l}kiewicz, Micha{\l}", |
|
booktitle = "Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion", |
|
month = may, |
|
year = "2022", |
|
address = "Dublin, Ireland", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://aclanthology.org/2022.ltedi-1.40", |
|
doi = "10.18653/v1/2022.ltedi-1.40", |
|
pages = "276--282", |
|
} |
|
``` |
