haiku.rag/BENCHMARKS.md
2025-06-25 18:18:28 +03:00

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# `haiku.rag` benchmarks
We use [repliqa](https://huggingface.co/datasets/ServiceNow/repliqa) for the evaluation of `haiku.rag`
* Recall
We load the `News Stories` from `repliqa_3` which is 1035 documents, using `tests/generate_benchmark_db.py`, using the `mxbai-embed-large` Ollama embeddings.
Subsequently, we run a search over the `question` for each row of the dataset and check whether we match the document that answers the question. The recall obtained is ~0.75 for matching in the top result, raising to ~0.75 for the top 3 results.