--- viewer: false language: - ace - amh - ara - arq - ary - bam - ban - bbc - ben - bjn - bos - bug - bul - ces - dan - deu - ell - eng - fas - fil - fin - fre - hau - heb - hin - hrv - hun - ibo - ind - ita - jav - jpn - kan - kin - kor - mad - mal - mar - min - mlt - nij - nor - pcm - pol - por - ron - rus - slk - slv - spa - sqi - srp - sun - swe - swh - tam - tel - tha - tso - tur - twi - vie - yor - zho tags: - Anti-Social - Emotion Recognition - Humor Detection - Irony - Sarcasm - Sentiment Analysis - Subjectivity Analysis - hate speech detection - offensive language detection task_categories: - text-classification extra_gated_fields: Full Name: text Official Email Address: text Affiliation: text Country: text I agree to ONLY use this dataset for non-commercial purposes: checkbox I agree to cite the SPARROW paper and all original papers: checkbox ---



Documentation

In this work, we introduce [**SPARROW**](https://arxiv.org/abs/2310.14557), SPARROW is a evaluation benchmark for sociopragmatic meaning understanding. SPARROW comprises 169 datasets covering 13 task types across six primary categories (e.g., anti-social language detection, emotion recognition). SPARROW datasets encompass 64 different languages originating from 12 language families representing 16 writing scripts. # How to Use SPARROW ### Request Access ### To obtain access to the SPARROW benchmark on Huggingface, follow the following steps: - Login on your Haggingface account - Request access * Please fill in your actual full name and affiliation (e.g., the name of your research institute). * Please use your official email address if it is available. ## Install Requirments ```shell pip install datasets transformers seqeval ``` ### Login with your Huggingface CLI ### You can get/manage your access tokens in your [settings](https://huggingface.co/docs/hub/security-tokens). ```shell export HUGGINGFACE_TOKEN="" huggingface-cli login --token $HUGGINGFACE_TOKEN ``` ## Submitting your results on SPARROW test We design a public leaderboard for scoring PLMs on SPARRAW. Our leaderboard is interactive and offers rich meta-data about the various datasets involved as well as the language models we evaluate. You can evalute your models using **SPARROW** leaderboard: **[https://sparrow.dlnlp.ai](https://sparrow.dlnlp.ai)** --- ## Citation If you use SPARROW for your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows: ```bibtex @inproceedings{zhang-etal-2023-skipped, title = "The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages", author = "Zhang, Chiyu and Khai Duy Doan and, Qisheng Liao and, Abdul-Mageed, Muhammad", booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)", year = "2023", publisher = "Association for Computational Linguistics", } ``` --- ## Acknowledgments We gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, Canadian Foundation for Innovation, [ComputeCanada](www.computecanada.ca) and [UBC ARC-Sockeye](https://doi.org/10.14288/SOCKEYE).