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---
language:
- en
widget:
- text: Call me today to earn some money mofos!
datasets:
- cardiffnlp/x_sensitive
license: mit
metrics:
- f1
pipeline_tag: text-classification
---
# twitter-roberta-large-sensitive-binary
This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for detecting sensitive content (binary classification) on the [_X-Sensitive_](https://huggingface.co/datasets/cardiffnlp/x_sensitive) dataset.
The original Twitter-based RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-large-2022-154m).
## Labels
```
"id2label": {
"0": "non-sensitive",
"1": "sensitive"
}
```
## Full classification example
```python
from transformers import pipeline
pipe = pipeline(model='cardiffnlp/twitter-roberta-large-sensitive-binary')
text = "Call me today to earn some money mofos!"
pipe(text)
```
Output:
```
[{'label': 'sensitive', 'score': 0.999821126461029}]
```
## BibTeX entry and citation info
```
@article{antypas2024sensitive,
title={Sensitive Content Classification in Social Media: A Holistic Resource and Evaluation},
author={Antypas, Dimosthenis and Sen, Indira and Perez-Almendros, Carla and Camacho-Collados, Jose and Barbieri, Francesco},
journal={arXiv preprint arXiv:2411.19832},
year={2024}
}
``` |