Mutarjim:利用小型語言模型推進阿拉伯語-英語雙向翻譯
Mutarjim: Advancing Bidirectional Arabic-English Translation with a Small Language Model
May 23, 2025
作者: Khalil Hennara, Muhammad Hreden, Mohamed Motaism Hamed, Zeina Aldallal, Sara Chrouf, Safwan AlModhayan
cs.AI
摘要
我們推出了Mutarjim,這是一個緊湊而強大的雙向阿拉伯語-英語翻譯語言模型。雖然大規模的語言模型(LLMs)在自然語言處理任務,包括機器翻譯方面,已展現出顯著的進展,但較小的模型也有其獨特優勢。基於這一洞察,我們開發了Mutarjim,它基於Kuwain-1.5B,這是一個專為阿拉伯語和英語設計的語言模型。儘管體積適中,Mutarjim在多個已建立的基準測試中超越了許多更大的模型,這得益於其優化的兩階段訓練方法和精心挑選的高質量訓練語料庫。實驗結果顯示,Mutarjim在性能上可與體積大20倍的模型相媲美,同時顯著降低了計算成本和訓練需求。我們還推出了Tarjama-25,這是一個新的基準測試,旨在克服現有阿拉伯語-英語基準數據集的局限性,如領域狹窄、句子長度短和英語源語偏見。Tarjama-25包含5,000對專家審查的句子對,涵蓋廣泛的領域,提供了一個更全面和平衡的評估框架。值得注意的是,Mutarjim在Tarjama-25的英語到阿拉伯語任務中達到了最先進的性能,甚至超越了像GPT-4o mini這樣更大且專有的模型。我們公開發布Tarjama-25,以支持未來的研究並推動阿拉伯語-英語翻譯系統的評估進展。
English
We introduce Mutarjim, a compact yet powerful language model for
bidirectional Arabic-English translation. While large-scale LLMs have shown
impressive progress in natural language processing tasks, including machine
translation, smaller models. Leveraging this insight, we developed Mutarjim
based on Kuwain-1.5B , a language model tailored for both Arabic and English.
Despite its modest size, Mutarjim outperforms much larger models on several
established benchmarks, achieved through an optimized two-phase training
approach and a carefully curated, high-quality training corpus.. Experimental
results show that Mutarjim rivals models up to 20 times larger while
significantly reducing computational costs and training requirements. We also
introduce Tarjama-25, a new benchmark designed to overcome limitations in
existing Arabic-English benchmarking datasets, such as domain narrowness, short
sentence lengths, and English-source bias. Tarjama-25 comprises 5,000
expert-reviewed sentence pairs and spans a wide range of domains, offering a
more comprehensive and balanced evaluation framework. Notably, Mutarjim
achieves state-of-the-art performance on the English-to-Arabic task in
Tarjama-25, surpassing even significantly larger and proprietary models like
GPT-4o mini. We publicly release Tarjama-25 to support future research and
advance the evaluation of Arabic-English translation systems.Summary
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