metadata
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 dataset. The original Twitter-based RoBERTa model can be found here.
Labels
"id2label": {
"0": "non-sensitive",
"1": "sensitive"
}
Full classification example
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
TBA