Investigating Techniques for a Deeper Understanding of Neural Machine Translation (NMT) Systems through Data Filtering and Fine-tuning Strategies

Lichao Zhu, Maria Zimina, Maud Bénard, Behnoosh Namdar, Nicolas Ballier, Guillaume Wisniewski, Jean-Baptiste Yunès


Abstract
In the context of this biomedical shared task, we have implemented data filters to enhance the selection of relevant training data for fine- tuning from the available training data sources. Specifically, we have employed textometric analysis to detect repetitive segments within the test set, which we have then used for re- fining the training data used to fine-tune the mBart-50 baseline model. Through this approach, we aim to achieve several objectives: developing a practical fine-tuning strategy for training biomedical in-domain fr<>en models, defining criteria for filtering in-domain training data, and comparing model predictions, fine-tuning data in accordance with the test set to gain a deeper insight into the functioning of Neural Machine Translation (NMT) systems.
Anthology ID:
2023.wmt-1.28
Volume:
Proceedings of the Eighth Conference on Machine Translation
Month:
December
Year:
2023
Address:
Singapore
Editors:
Philipp Koehn, Barry Haddow, Tom Kocmi, Christof Monz
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
275–281
Language:
URL:
https://aclanthology.org/2023.wmt-1.28
DOI:
10.18653/v1/2023.wmt-1.28
Bibkey:
Cite (ACL):
Lichao Zhu, Maria Zimina, Maud Bénard, Behnoosh Namdar, Nicolas Ballier, Guillaume Wisniewski, and Jean-Baptiste Yunès. 2023. Investigating Techniques for a Deeper Understanding of Neural Machine Translation (NMT) Systems through Data Filtering and Fine-tuning Strategies. In Proceedings of the Eighth Conference on Machine Translation, pages 275–281, Singapore. Association for Computational Linguistics.
Cite (Informal):
Investigating Techniques for a Deeper Understanding of Neural Machine Translation (NMT) Systems through Data Filtering and Fine-tuning Strategies (Zhu et al., WMT 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-1/2023.wmt-1.28.pdf