metadata
datasets:
- FIdo-AI/ua-news
language:
- uk
metrics:
- rouge
library_name: transformers
pipeline_tag: summarization
tags:
- news
Model Card for Model ID
Model Summary
The mT5-multilingual-XLSum model was fine-tuned on the UA-News dataset to generate concise and accurate news headlines in Ukrainian language.
Training
- Epochs: 4
- Batch Size: 4
- Learning Rate: 4e-5
Evaluation
- Metrics: The model's performance on the test set.
- ROUGE-1: 0.2452
- ROUGE-2: 0.1075
- ROUGE-L: 0.2348
- BERTScore: 0.7573
Usage
from transformers import pipeline
summarizer = pipeline("summarization", model="yelyah/mT5-XLSUM-ua-news")
article = "Your news article text here."
summary = summarizer(article)
print(summary)