Greek RAG tuning lifts retrieval to 0.835

A Modern Greek RAG project raised its Nemotron 1B embedder’s nDCG@10 from 0.362 to 0.835 after fine-tuning on 65,773 retrieval pairs, while its adapted reader lifted judged answer correctness from 29.4% to 66.9%. The HERA benchmark paper also found that untuned multilingual dense retrievers lost to BM25 on specialist Greek corpora. For operators, the result reinforces the lesson from Qwen’s expensive model-hosting trade-off: test a cheap lexical baseline, then spend on language- and domain-specific adaptation rather than assuming a larger general model will retrieve better.