all AI news
Human Evaluation of English--Irish Transformer-Based NMT
March 6, 2024, 5:47 a.m. | S\'eamus Lankford, Haithem Afli, Andy Way
cs.CL updates on arXiv.org arxiv.org
Abstract: In this study, a human evaluation is carried out on how hyperparameter settings impact the quality of Transformer-based Neural Machine Translation (NMT) for the low-resourced English--Irish pair. SentencePiece models using both Byte Pair Encoding (BPE) and unigram approaches were appraised. Variations in model architectures included modifying the number of layers, evaluating the optimal number of heads for attention and testing various regularisation techniques. The greatest performance improvement was recorded for a Transformer-optimized model with a …
abstract architectures arxiv cs.ai cs.cl encoding english evaluation human hyperparameter impact low machine machine translation neural machine translation quality study transformer translation type
More from arxiv.org / cs.CL updates on arXiv.org
Benchmarking LLMs via Uncertainty Quantification
1 day, 16 hours ago |
arxiv.org
CARE: Extracting Experimental Findings From Clinical Literature
1 day, 16 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Intern Large Language Models Planning (f/m/x)
@ BMW Group | Munich, DE
Data Engineer Analytics
@ Meta | Menlo Park, CA | Remote, US