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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)
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Dataset used to train yelyah/mT5-XLSUM-ua-news