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3db4bdd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | BEIR
====
`BEIR <https://github.com/beir-cellar/beir>`_ (Benchmarking-IR) is a heterogeneous evaluation benchmark for information retrieval.
It is designed for evaluating the performance of NLP-based retrieval models and widely used by research of modern embedding models.
You can evaluate model's performance on the BEIR benchmark by running our provided shell script:
.. code:: bash
chmod +x /examples/evaluation/beir/eval_beir.sh
./examples/evaluation/beir/eval_beir.sh
Or by running:
.. code:: bash
python -m FlagEmbedding.evaluation.beir \
--eval_name beir \
--dataset_dir ./beir/data \
--dataset_names fiqa arguana cqadupstack \
--splits test dev \
--corpus_embd_save_dir ./beir/corpus_embd \
--output_dir ./beir/search_results \
--search_top_k 1000 \
--rerank_top_k 100 \
--cache_path /root/.cache/huggingface/hub \
--overwrite False \
--k_values 10 100 \
--eval_output_method markdown \
--eval_output_path ./beir/beir_eval_results.md \
--eval_metrics ndcg_at_10 recall_at_100 \
--ignore_identical_ids True \
--embedder_name_or_path BAAI/bge-large-en-v1.5 \
--reranker_name_or_path BAAI/bge-reranker-v2-m3 \
--devices cuda:0 cuda:1 \
--reranker_max_length 1024 \
change the embedder, devices and cache directory to your preference.
.. toctree::
:hidden:
beir/arguments
beir/data_loader
beir/evaluator
beir/runner |