🚀 HATE-ITA Base
HATE-ITA is a binary hate speech classification model designed for Italian social media text. It plays a crucial role in identifying and countering online hate speech in the Italian language.
🚀 Quick Start
HATE-ITA is a binary hate speech classification model for Italian social media text. You can quickly start using it with the provided code examples.
✨ Features
- Multi - language Training: HATE-ITA is a set of multi - language models trained on a large set of English data and available Italian datasets, which performs better than mono - lingual models.
- Good Adaptability: It seems to adapt well to language - specific slurs.
📦 Installation
No specific installation steps are provided in the original document.
💻 Usage Examples
Basic Usage
from transformers import pipeline
classifier = pipeline("text-classification",model='MilaNLProc/hate-ita',top_k=2)
prediction = classifier("ti odio")
print(prediction)
📚 Documentation
Abstract
Online hate speech is a dangerous phenomenon that can (and should) be promptly counteracted properly. While Natural Language Processing has been successfully used for the purpose, many of the research efforts are directed toward the English language. This choice severely limits the classification power in non - English languages. In this paper, we test several learning frameworks for identifying hate speech in Italian text. We release HATE-ITA, a set of multi - language models trained on a large set of English data and available Italian datasets. HATE-ITA performs better than mono - lingual models and seems to adapt well also on language - specific slurs. We believe our findings will encourage research in other mid - to - low resource communities and provide a valuable benchmarking tool for the Italian community.
Model
This model is the fine - tuned version of the XLM - T model.
Property |
Details |
Model Type |
The fine - tuned version of the XLM - T model |
Download |
|
hate-ita |
Link |
hate-ita-xlm-r-base |
Link |
hate-ita-xlm-r-large |
Link |
Results
This model had an F1 of 0.83 on the test set.
Citation
Please use the following BibTeX entry if you use this model in your project:
@inproceedings{nozza-etal-2022-hate-ita,
title = {{HATE-ITA}: Hate Speech Detection in Italian Social Media Text},
author = "Nozza, Debora and Bianchi, Federico and Attanasio, Giuseppe",
booktitle = "Proceedings of the 6th Workshop on Online Abuse and Harms",
year = "2022",
publisher = "Association for Computational Linguistics"
}
Ethical Statement
While promising, the results in this work should not be interpreted as a definitive assessment of the performance of hate speech detection in Italian. We are unsure if our model can maintain a stable and fair precision across the different targets and categories. HATE-ITA might overlook some sensible details, which practitioners should treat with care.
📄 License
GNU GPLv3
Authors
Debora Nozza •
Federico Bianchi •
Giuseppe Attanasio
Widget Examples
- Hate Speech Classification 1: "Ci sono dei bellissimi capibara!"
- Hate Speech Classification 2: "Sei una testa di cazzo!!"
- Hate Speech Classification 3: "Ti odio!"