Abstractive summary generation is a challenging task that requires the model
to comprehend the source text and generate a concise and coherent summary that
captures the essential information. In this paper, we explore the use of an
encoder/decoder approach for abstractive summary generation in the Urdu
language. We employ a transformer-based model that utilizes self-attention
mechanisms to encode the input text and generate a summary. Our experiments
show that our model can produce summaries that are grammatically correct and
semantically meaningful. We evaluate our model on a publicly available dataset
and achieve state-of-the-art results in terms of Rouge scores. We also conduct
a qualitative analysis of our model's output to assess its effectiveness and
limitations. Our findings suggest that the encoder/decoder approach is a
promising method for abstractive summary generation in Urdu and can be extended
to other languages with suitable modifications.

本文探讨了在乌尔都语的抽象性摘要生成中，使用编码器 / 解码器方法。我们利用一种基于变压器的模型来编码输入文本并生成摘要，实验表明我们的模型可以生成语法正确、意义明确的摘要，并在公开数据集上取得了最先进的 ROUGE 得分结果。我们还对模型输出进行了定性分析，评估其有效性和局限性，发现编码器 / 解码器方法在乌尔都语的抽象性摘要生成中是一种有前途的方法，并且可以通过适当的修改扩展到其他语言。