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---
language:
- en
license: mit
datasets:
- cardiffnlp/super_tweeteval
pipeline_tag: text-classification
---
# cardiffnlp/twitter-roberta-large-topic-latest
This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for topic classification (multilabel classification) on the _TweetTopic_ 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-large-2022-154m).
## Labels
<code>
"id2label": {
"0": "arts_&_culture",
"1": "business_&_entrepreneurs",
"2": "celebrity_&_pop_culture",
"3": "diaries_&_daily_life",
"4": "family",
"5": "fashion_&_style",
"6": "film_tv_&_video",
"7": "fitness_&_health",
"8": "food_&_dining",
"9": "gaming",
"10": "learning_&_educational",
"11": "music",
"12": "news_&_social_concern",
"13": "other_hobbies",
"14": "relationships",
"15": "science_&_technology",
"16": "sports",
"17": "travel_&_adventure",
"18": "youth_&_student_life"
}
</code>
## Example
```python
from transformers import pipeline
text = "So @AB is just the latest victim of the madden curse. If you’re on the cover of that game your career will take a turn for the worse"
pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-large-topic-latest", return_all_scores=True)
predictions = pipe(text)[0]
predictions = [x for x in predictions if x['score'] > 0.5]
predictions
>> [{'label': 'sports', 'score': 0.99379563331604}]
```
## 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}
}
``` |