Pyserini Reproductions: MIRACL

This page provides two-click reproductions* for a number of experimental runs on the MIRACL dataset. Instructions for programmatic execution are shown at the bottom of this page. The dataset is described in the following paper:

Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, Ehsan Kamalloo, David Alfonso-Hermelo, Xiaoguang Li, Qun Liu, Mehdi Rezagholizadeh, and Jimmy Lin. MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages. Transactions of the Association for Computational Linguistics, 11:1114–1131, 2023.

Many of the models presented on this page are described in the following paper:

Xinyu Zhang, Kelechi Ogueji, Xueguang Ma, and Jimmy Lin. Towards Best Practices for Training Multilingual Dense Retrieval Models. ACM Transactions on Information Systems, 42(2), Article No. 39, 2023.

Key:

nDCG@10, dev queries ar bn en es fa fi fr hi id ja ko ru sw te th zh de yo avg
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ar \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar \
  --output run.miracl.bm25.ar.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ar-dev \
  run.miracl.bm25.ar.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language bn \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn \
  --output run.miracl.bm25.bn.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-bn-dev \
  run.miracl.bm25.bn.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language en \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en \
  --output run.miracl.bm25.en.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-en-dev \
  run.miracl.bm25.en.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language es \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es \
  --output run.miracl.bm25.es.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-es-dev \
  run.miracl.bm25.es.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language fa \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa \
  --output run.miracl.bm25.fa.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fa-dev \
  run.miracl.bm25.fa.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language fi \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi \
  --output run.miracl.bm25.fi.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fi-dev \
  run.miracl.bm25.fi.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language fr \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr \
  --output run.miracl.bm25.fr.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fr-dev \
  run.miracl.bm25.fr.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language hi \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi \
  --output run.miracl.bm25.hi.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-hi-dev \
  run.miracl.bm25.hi.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language id \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id \
  --output run.miracl.bm25.id.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-id-dev \
  run.miracl.bm25.id.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ja \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja \
  --output run.miracl.bm25.ja.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ja-dev \
  run.miracl.bm25.ja.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ko \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko \
  --output run.miracl.bm25.ko.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ko-dev \
  run.miracl.bm25.ko.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ru \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru \
  --output run.miracl.bm25.ru.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ru-dev \
  run.miracl.bm25.ru.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language sw \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw \
  --output run.miracl.bm25.sw.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-sw-dev \
  run.miracl.bm25.sw.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language te \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te \
  --output run.miracl.bm25.te.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-te-dev \
  run.miracl.bm25.te.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language th \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th \
  --output run.miracl.bm25.th.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-th-dev \
  run.miracl.bm25.th.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language zh \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh \
  --output run.miracl.bm25.zh.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-zh-dev \
  run.miracl.bm25.zh.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language de \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de \
  --output run.miracl.bm25.de.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-de-dev \
  run.miracl.bm25.de.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 --pretokenized \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo \
  --output run.miracl.bm25.yo.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-yo-dev \
  run.miracl.bm25.yo.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ar-dev \
  run.miracl.mdpr-tied-pft-msmarco.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-bn-dev \
  run.miracl.mdpr-tied-pft-msmarco.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-en-dev \
  run.miracl.mdpr-tied-pft-msmarco.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-es-dev \
  run.miracl.mdpr-tied-pft-msmarco.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fa-dev \
  run.miracl.mdpr-tied-pft-msmarco.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fi-dev \
  run.miracl.mdpr-tied-pft-msmarco.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fr-dev \
  run.miracl.mdpr-tied-pft-msmarco.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-hi-dev \
  run.miracl.mdpr-tied-pft-msmarco.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-id-dev \
  run.miracl.mdpr-tied-pft-msmarco.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ja-dev \
  run.miracl.mdpr-tied-pft-msmarco.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ko-dev \
  run.miracl.mdpr-tied-pft-msmarco.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ru-dev \
  run.miracl.mdpr-tied-pft-msmarco.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-sw-dev \
  run.miracl.mdpr-tied-pft-msmarco.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-te-dev \
  run.miracl.mdpr-tied-pft-msmarco.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-th-dev \
  run.miracl.mdpr-tied-pft-msmarco.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-zh-dev \
  run.miracl.mdpr-tied-pft-msmarco.zh.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.de.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-de-dev \
  run.miracl.mdpr-tied-pft-msmarco.de.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.yo.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-yo-dev \
  run.miracl.mdpr-tied-pft-msmarco.yo.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ar.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ar.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ar.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ar-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ar.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.bn.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.bn.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.bn.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-bn-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.bn.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.en.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.en.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.en.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-en-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.en.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.es.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.es.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.es.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-es-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.es.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.fa.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.fa.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fa.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fa-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fa.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.fi.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.fi.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fi.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fi-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fi.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.fr.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.fr.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fr.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fr-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fr.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.hi.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.hi.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.hi.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-hi-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.hi.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.id.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.id.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.id.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-id-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.id.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ja.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ja.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ja.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ja-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ja.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ko.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ko.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ko.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ko-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ko.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ru.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ru.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ru.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ru-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ru.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.sw.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.sw.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.sw.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-sw-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.sw.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.te.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.te.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.te.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-te-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.te.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.th.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.th.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.th.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-th-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.th.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.zh.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.zh.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.zh.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-zh-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.zh.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.de.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.de.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.de.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-de-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.de.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.yo.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.yo.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.yo.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-yo-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.yo.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ar-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-bn-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-en-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-es-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fa-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fr-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-hi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-id-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ja-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ko-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ru-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-sw-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-te-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-th-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-zh-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.zh.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.de.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-de-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.de.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.yo.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-yo-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.yo.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ar \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mdpr-tied-pft-msmarco-ft-miracl-ar \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ar-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-bn \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mdpr-tied-pft-msmarco-ft-miracl-bn \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-bn-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-en \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mdpr-tied-pft-msmarco-ft-miracl-en \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-en-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-es \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mdpr-tied-pft-msmarco-ft-miracl-es \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-es-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-fa \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mdpr-tied-pft-msmarco-ft-miracl-fa \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fa-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-fi \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mdpr-tied-pft-msmarco-ft-miracl-fi \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-fr \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mdpr-tied-pft-msmarco-ft-miracl-fr \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fr-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-hi \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mdpr-tied-pft-msmarco-ft-miracl-hi \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-hi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-id \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mdpr-tied-pft-msmarco-ft-miracl-id \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-id-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ja \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mdpr-tied-pft-msmarco-ft-miracl-ja \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ja-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ko \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mdpr-tied-pft-msmarco-ft-miracl-ko \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ko-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ru \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mdpr-tied-pft-msmarco-ft-miracl-ru \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ru-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-sw \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mdpr-tied-pft-msmarco-ft-miracl-sw \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-sw-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-te \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mdpr-tied-pft-msmarco-ft-miracl-te \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-te-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-th \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mdpr-tied-pft-msmarco-ft-miracl-th \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-th-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-zh \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mdpr-tied-pft-msmarco-ft-miracl-zh \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-zh-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.zh.dev.txt
Command to generate run:

Evaluation commands:
Command to generate run:

Evaluation commands:
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ar-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-bn-dev \
  run.miracl.mcontriever-tied-pft-msmarco.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-en-dev \
  run.miracl.mcontriever-tied-pft-msmarco.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-es-dev \
  run.miracl.mcontriever-tied-pft-msmarco.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fa-dev \
  run.miracl.mcontriever-tied-pft-msmarco.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fi-dev \
  run.miracl.mcontriever-tied-pft-msmarco.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-fr-dev \
  run.miracl.mcontriever-tied-pft-msmarco.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-hi-dev \
  run.miracl.mcontriever-tied-pft-msmarco.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-id-dev \
  run.miracl.mcontriever-tied-pft-msmarco.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ja-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ko-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-ru-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-sw-dev \
  run.miracl.mcontriever-tied-pft-msmarco.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-te-dev \
  run.miracl.mcontriever-tied-pft-msmarco.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-th-dev \
  run.miracl.mcontriever-tied-pft-msmarco.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-zh-dev \
  run.miracl.mcontriever-tied-pft-msmarco.zh.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.de.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-de-dev \
  run.miracl.mcontriever-tied-pft-msmarco.de.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.yo.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -M 100 -m ndcg_cut.10 miracl-v1.0-yo-dev \
  run.miracl.mcontriever-tied-pft-msmarco.yo.dev.txt
Recall@100, dev queries ar bn en es fa fi fr hi id ja ko ru sw te th zh de yo avg
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ar \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar \
  --output run.miracl.bm25.ar.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ar-dev \
  run.miracl.bm25.ar.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language bn \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn \
  --output run.miracl.bm25.bn.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-bn-dev \
  run.miracl.bm25.bn.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language en \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en \
  --output run.miracl.bm25.en.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-en-dev \
  run.miracl.bm25.en.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language es \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es \
  --output run.miracl.bm25.es.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-es-dev \
  run.miracl.bm25.es.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language fa \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa \
  --output run.miracl.bm25.fa.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fa-dev \
  run.miracl.bm25.fa.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language fi \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi \
  --output run.miracl.bm25.fi.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fi-dev \
  run.miracl.bm25.fi.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language fr \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr \
  --output run.miracl.bm25.fr.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fr-dev \
  run.miracl.bm25.fr.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language hi \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi \
  --output run.miracl.bm25.hi.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-hi-dev \
  run.miracl.bm25.hi.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language id \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id \
  --output run.miracl.bm25.id.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-id-dev \
  run.miracl.bm25.id.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ja \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja \
  --output run.miracl.bm25.ja.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ja-dev \
  run.miracl.bm25.ja.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ko \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko \
  --output run.miracl.bm25.ko.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ko-dev \
  run.miracl.bm25.ko.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language ru \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru \
  --output run.miracl.bm25.ru.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ru-dev \
  run.miracl.bm25.ru.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language sw \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw \
  --output run.miracl.bm25.sw.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-sw-dev \
  run.miracl.bm25.sw.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language te \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te \
  --output run.miracl.bm25.te.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-te-dev \
  run.miracl.bm25.te.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language th \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th \
  --output run.miracl.bm25.th.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-th-dev \
  run.miracl.bm25.th.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language zh \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh \
  --output run.miracl.bm25.zh.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-zh-dev \
  run.miracl.bm25.zh.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 \
  --language de \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de \
  --output run.miracl.bm25.de.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-de-dev \
  run.miracl.bm25.de.dev.txt
Command to generate run:
python -m pyserini.search.lucene \
  --threads 16 --batch-size 128 --pretokenized \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo \
  --output run.miracl.bm25.yo.dev.txt \
  --bm25 --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-yo-dev \
  run.miracl.bm25.yo.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ar-dev \
  run.miracl.mdpr-tied-pft-msmarco.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-bn-dev \
  run.miracl.mdpr-tied-pft-msmarco.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-en-dev \
  run.miracl.mdpr-tied-pft-msmarco.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-es-dev \
  run.miracl.mdpr-tied-pft-msmarco.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fa-dev \
  run.miracl.mdpr-tied-pft-msmarco.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fi-dev \
  run.miracl.mdpr-tied-pft-msmarco.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fr-dev \
  run.miracl.mdpr-tied-pft-msmarco.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-hi-dev \
  run.miracl.mdpr-tied-pft-msmarco.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-id-dev \
  run.miracl.mdpr-tied-pft-msmarco.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ja-dev \
  run.miracl.mdpr-tied-pft-msmarco.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ko-dev \
  run.miracl.mdpr-tied-pft-msmarco.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ru-dev \
  run.miracl.mdpr-tied-pft-msmarco.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-sw-dev \
  run.miracl.mdpr-tied-pft-msmarco.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-te-dev \
  run.miracl.mdpr-tied-pft-msmarco.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-th-dev \
  run.miracl.mdpr-tied-pft-msmarco.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-zh-dev \
  run.miracl.mdpr-tied-pft-msmarco.zh.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.de.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-de-dev \
  run.miracl.mdpr-tied-pft-msmarco.de.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo-mdpr-tied-pft-msmarco \
  --output run.miracl.mdpr-tied-pft-msmarco.yo.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-yo-dev \
  run.miracl.mdpr-tied-pft-msmarco.yo.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ar.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ar.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ar.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ar-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ar.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.bn.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.bn.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.bn.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-bn-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.bn.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.en.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.en.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.en.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-en-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.en.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.es.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.es.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.es.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-es-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.es.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.fa.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.fa.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fa.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fa-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fa.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.fi.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.fi.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fi.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fi-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fi.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.fr.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.fr.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fr.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fr-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.fr.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.hi.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.hi.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.hi.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-hi-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.hi.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.id.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.id.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.id.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-id-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.id.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ja.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ja.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ja.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ja-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ja.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ko.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ko.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ko.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ko-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ko.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.ru.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.ru.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ru.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ru-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.ru.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.sw.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.sw.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.sw.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-sw-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.sw.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.te.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.te.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.te.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-te-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.te.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.th.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.th.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.th.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-th-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.th.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.zh.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.zh.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.zh.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-zh-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.zh.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.de.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.de.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.de.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-de-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.de.dev.txt
Command to generate run:
python -m pyserini.fusion \
  --runs  run.miracl.bm25.yo.dev.top1000.txt run.miracl.mdpr-tied-pft-msmarco.yo.dev.top1000.txt \
  --output run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.yo.dev.txt --method interpolation --alpha 0.5 --depth 1000 --k 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-yo-dev \
  run.miracl.bm25-mdpr-tied-pft-msmarco-hybrid.yo.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ar-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-bn-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-en-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-es-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fa-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fr-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-hi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-id-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ja-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ko-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ru-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-sw-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-te-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-th-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-zh-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.zh.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.de.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-de-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.de.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-all \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo-mdpr-tied-pft-msmarco-ft-all \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-all.yo.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-yo-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-all.yo.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ar \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mdpr-tied-pft-msmarco-ft-miracl-ar \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ar-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-bn \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mdpr-tied-pft-msmarco-ft-miracl-bn \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-bn-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-en \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mdpr-tied-pft-msmarco-ft-miracl-en \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-en-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-es \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mdpr-tied-pft-msmarco-ft-miracl-es \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-es-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-fa \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mdpr-tied-pft-msmarco-ft-miracl-fa \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fa-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-fi \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mdpr-tied-pft-msmarco-ft-miracl-fi \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-fr \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mdpr-tied-pft-msmarco-ft-miracl-fr \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fr-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-hi \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mdpr-tied-pft-msmarco-ft-miracl-hi \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-hi-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-id \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mdpr-tied-pft-msmarco-ft-miracl-id \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-id-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ja \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mdpr-tied-pft-msmarco-ft-miracl-ja \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ja-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ko \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mdpr-tied-pft-msmarco-ft-miracl-ko \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ko-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-ru \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mdpr-tied-pft-msmarco-ft-miracl-ru \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ru-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-sw \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mdpr-tied-pft-msmarco-ft-miracl-sw \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-sw-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-te \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mdpr-tied-pft-msmarco-ft-miracl-te \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-te-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-th \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mdpr-tied-pft-msmarco-ft-miracl-th \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-th-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class auto \
  --encoder castorini/mdpr-tied-pft-msmarco-ft-miracl-zh \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mdpr-tied-pft-msmarco-ft-miracl-zh \
  --output run.miracl.mdpr-tied-pft-msmarco-ft-miracl.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-zh-dev \
  run.miracl.mdpr-tied-pft-msmarco-ft-miracl.zh.dev.txt
Command to generate run:

Evaluation commands:
Command to generate run:

Evaluation commands:
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ar-dev \
  --index miracl-v1.0-ar-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ar.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ar-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ar.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-bn-dev \
  --index miracl-v1.0-bn-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.bn.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-bn-dev \
  run.miracl.mcontriever-tied-pft-msmarco.bn.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-en-dev \
  --index miracl-v1.0-en-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.en.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-en-dev \
  run.miracl.mcontriever-tied-pft-msmarco.en.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-es-dev \
  --index miracl-v1.0-es-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.es.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-es-dev \
  run.miracl.mcontriever-tied-pft-msmarco.es.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-fa-dev \
  --index miracl-v1.0-fa-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.fa.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fa-dev \
  run.miracl.mcontriever-tied-pft-msmarco.fa.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-fi-dev \
  --index miracl-v1.0-fi-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.fi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fi-dev \
  run.miracl.mcontriever-tied-pft-msmarco.fi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-fr-dev \
  --index miracl-v1.0-fr-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.fr.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-fr-dev \
  run.miracl.mcontriever-tied-pft-msmarco.fr.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-hi-dev \
  --index miracl-v1.0-hi-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.hi.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-hi-dev \
  run.miracl.mcontriever-tied-pft-msmarco.hi.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-id-dev \
  --index miracl-v1.0-id-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.id.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-id-dev \
  run.miracl.mcontriever-tied-pft-msmarco.id.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ja-dev \
  --index miracl-v1.0-ja-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ja.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ja-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ja.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ko-dev \
  --index miracl-v1.0-ko-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ko.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ko-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ko.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-ru-dev \
  --index miracl-v1.0-ru-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.ru.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-ru-dev \
  run.miracl.mcontriever-tied-pft-msmarco.ru.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-sw-dev \
  --index miracl-v1.0-sw-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.sw.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-sw-dev \
  run.miracl.mcontriever-tied-pft-msmarco.sw.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-te-dev \
  --index miracl-v1.0-te-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.te.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-te-dev \
  run.miracl.mcontriever-tied-pft-msmarco.te.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-th-dev \
  --index miracl-v1.0-th-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.th.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-th-dev \
  run.miracl.mcontriever-tied-pft-msmarco.th.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-zh-dev \
  --index miracl-v1.0-zh-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.zh.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-zh-dev \
  run.miracl.mcontriever-tied-pft-msmarco.zh.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-de-dev \
  --index miracl-v1.0-de-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.de.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-de-dev \
  run.miracl.mcontriever-tied-pft-msmarco.de.dev.txt
Command to generate run:
python -m pyserini.search.faiss \
  --threads 16 --batch-size 512 \
  --encoder-class contriever \
  --encoder facebook/mcontriever-msmarco \
  --topics miracl-v1.0-yo-dev \
  --index miracl-v1.0-yo-mcontriever-pft-msmarco \
  --output run.miracl.mcontriever-tied-pft-msmarco.yo.dev.txt --hits 1000
Evaluation commands:
python -m pyserini.eval.trec_eval \
  -c -m recall.100 miracl-v1.0-yo-dev \
  run.miracl.mcontriever-tied-pft-msmarco.yo.dev.txt

Programmatic Execution

All experimental runs shown in the above table can be programmatically executed based on the instructions below. To list all the experimental conditions:

python -m pyserini.2cr.miracl --list-conditions

Run all languages for a specific condition and show commands:

python -m pyserini.2cr.miracl --condition bm25 --display-commands

Run a particular language for a specific condition and show commands:

python -m pyserini.2cr.miracl --condition bm25 --language ko --display-commands

Run all languages for all conditions and show commands:

python -m pyserini.2cr.miracl --all --display-commands

With the above commands, run files will be placed in the current directory. Use the option --directory runs to place the runs in a sub-directory.

For a specific condition, just show the commands and do not run:

python -m pyserini.2cr.miracl --condition bm25 --display-commands --dry-run

This will generate exactly the commands for a specific condition above (corresponding to a row in the table).

For a specific condition and language, just show the commands and do not run:

python -m pyserini.2cr.miracl --condition bm25 --language ko --display-commands --dry-run

For all conditions, just show the commands and do not run and skip evaluation:

python -m pyserini.2cr.miracl --all --display-commands --dry-run --skip-eval

Finally, to generate this page:

python -m pyserini.2cr.miracl --generate-report --output docs/2cr/miracl.html

The output file miracl.html should be identical to this page.