| language: | |
| - en | |
| license: mit | |
| datasets: | |
| - cardiffnlp/super_tweeteval | |
| pipeline_tag: text-classification | |
| # cardiffnlp/twitter-roberta-base-hate-latest-st | |
| This is a RoBERTa-base model trained on 154M tweets until the end of December 2022 and finetuned for hate speech detection (multiclass classification) on the _TweetHate_ dataset of [SuperTweetEval](https://huggingface.co/datasets/cardiffnlp/super_tweeteval). | |
| The original Twitter-based RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m). | |
| # Labels | |
| <code> | |
| "id2label": { | |
| "0": "hate_gender", | |
| "1": "hate_race", | |
| "2": "hate_sexuality", | |
| "3": "hate_religion", | |
| "4": "hate_origin", | |
| "5": "hate_disability", | |
| "6": "hate_age", | |
| "7": "not_hate" | |
| } | |
| </code> | |
| ## Example | |
| ```python | |
| from transformers import pipeline | |
| text = 'Eid Mubarak Everyone!!! ❤ May Allah unite all Muslims, show us the right path, and bless us with good health.❣' | |
| pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-base-hate-latest-st") | |
| pipe(text) | |
| >> [{'label': 'not_hate', 'score': 0.9997966885566711}] | |
| ``` | |
| ## Citation Information | |
| Please cite the [reference paper](https://arxiv.org/abs/2310.14757) if you use this model. | |
| ```bibtex | |
| @inproceedings{antypas2023supertweeteval, | |
| title={SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research}, | |
| author={Dimosthenis Antypas and Asahi Ushio and Francesco Barbieri and Leonardo Neves and Kiamehr Rezaee and Luis Espinosa-Anke and Jiaxin Pei and Jose Camacho-Collados}, | |
| booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023}, | |
| year={2023} | |
| } | |
| ``` |