metadata
license: cc-by-4.0
language:
- en
pipeline_tag: text-classification
tags:
- distilroberta
- topic
- news
Fine-tuned distilroberta-base for detecting whether news is from a wire service
Model Description
This model is a finetuned distilroberta-base, for classifying whether news articles are from a wire service.
How to Use
from transformers import pipeline
classifier = pipeline("text-classification", model="dell-research-harvard/wire-classifier")
classifier("Washington (AP) Two men died in a car crash")
Training data
The model was trained on a hand-labelled sample of data from the NEWSWIRE dataset.
Split | Size |
---|---|
Train | 1,459 |
Dev | 336 |
Test | 448 |
Test set results
Metric | Result |
---|---|
F1 | 0.96 |
Accuracy | |
Precision | |
Recall |
Citation Information
You can cite this dataset using
@misc{silcock2024newswirelargescalestructureddatabase,
title={Newswire: A Large-Scale Structured Database of a Century of Historical News},
author={Emily Silcock and Abhishek Arora and Luca D'Amico-Wong and Melissa Dell},
year={2024},
eprint={2406.09490},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2406.09490},
}
Applications
We applied this model to a century of historical news articles. You can see all the classifications in the NEWSWIRE dataset.