mishbahul11/nerds-nits-opus-mt-ar-en-finetuned-wmt2026

This model is a fine-tuned version of `Helsinki-NLP/opus-mt-tc-big-ar-en`, adapted for Arabic→English translation as part of the NERDS-NITS submission to the WMT 2026 Low-Resource Arabic–Asian Language Translation Shared Task.

Model Description

• —Architecture: Marian Transformer-big (6-layer encoder, 6-layer decoder, hidden size 1024, feed-forward dimension 4096, 16 attention heads per layer, ~240M parameters)
• —Tokenization: SentencePiece (inherited from the original OPUS-MT checkpoint, trained on the OPUS parallel corpus)
• —Base model: Helsinki-NLP/opus-mt-tc-big-ar-en
• —Fine-tuning framework: Hugging Face Seq2SeqTrainer, minimizing sequence-to-sequence cross-entropy loss
• —Task: Arabic → English machine translation
• —Paper: NERDS-NITS at WMT 2026: Pivot-Based and Direct Neural Machine Translation for Arabic–Asian Low-Resource Language Pairs

Training Data

Fine-tuned on the WMT 2026 Arabic–English parallel corpus.

Evaluation Results

Devtest set

Official challenge test set (WMT 2026 organizers)

Acknowledgments

We thank the WMT 2026 shared task organizers for providing the datasets and evaluation infrastructure used in this work.