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======
`MIRACL <https://project-miracl.github.io/>`_ (Multilingual Information Retrieval Across a Continuum of Languages)
is an WSDM 2023 Cup challenge that focuses on search across 18 different languages.
They release a multilingual retrieval dataset containing the train and dev set for 16 "known languages" and only dev set for 2 "surprise languages".
The topics are generated by native speakers of each language, who also label the relevance between the topics and a given document list.
You can found the `dataset <https://huggingface.co/datasets/miracl/miracl-corpus>`_ on HuggingFace.
You can evaluate model's performance on MIRACL simply by running our provided shell script:
.. code:: bash
chmod +x /examples/evaluation/miracl/eval_miracl.sh
./examples/evaluation/miracl/eval_miracl.sh
Or by running:
.. code:: bash
python -m FlagEmbedding.evaluation.miracl \
--eval_name miracl \
--dataset_dir ./miracl/data \
--dataset_names bn hi sw te th yo \
--splits dev \
--corpus_embd_save_dir ./miracl/corpus_embd \
--output_dir ./miracl/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 ./miracl/miracl_eval_results.md \
--eval_metrics ndcg_at_10 recall_at_100 \
--embedder_name_or_path BAAI/bge-m3 \
--reranker_name_or_path BAAI/bge-reranker-v2-m3 \
--devices cuda:0 cuda:1 \
--cache_dir /root/.cache/huggingface/hub \
--reranker_max_length 1024
change the embedder, reranker, devices and cache directory to your preference.
.. toctree::
:hidden:
miracl/data_loader
miracl/runner |