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---
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
```python
from transformers import pipeline
summarizer = pipeline("summarization", model="yelyah/mT5-XLSUM-ua-news")
article = "Your news article text here."
summary = summarizer(article)
print(summary)
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