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Anserini Fatjar Regresions (v0.35.0)

Fetch the fatjar:

wget https://repo1.maven.org/maven2/io/anserini/anserini/0.35.0/anserini-0.35.0-fatjar.jar

MS MARCO V1 Passage

Currently, Anserini provides support for the following models:

  • BM25
  • SPLADE++ EnsembleDistil: pre-encoded queries and ONNX query encoding
  • cosDPR-distil: pre-encoded queries and ONNX query encoding
  • BGE-base-en-v1.5: pre-encoded queries and ONNX query encoding

The following snippet will generate the complete set of results for MS MARCO V1 Passage:

# BM25
TOPICS=(msmarco-v1-passage-dev dl19-passage dl20-passage); for t in "${TOPICS[@]}"
do
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index msmarco-v1-passage -topics ${t} -output run.${t}.bm25.txt -threads 16 -bm25
done

# SPLADE++ ED
TOPICS=(msmarco-v1-passage-dev dl19-passage dl20-passage); for t in "${TOPICS[@]}"
do
    # Using pre-encoded queries
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index msmarco-v1-passage-splade-pp-ed -topics ${t}-splade-pp-ed -output run.${t}.splade-pp-ed-pre.txt -threads 16 -impact -pretokenized
    # Using ONNX
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index msmarco-v1-passage-splade-pp-ed -topics ${t} -encoder SpladePlusPlusEnsembleDistil -output run.${t}.splade-pp-ed-onnx.txt -threads 16 -impact -pretokenized
done

# cosDPR-distil
TOPICS=(msmarco-v1-passage-dev dl19-passage dl20-passage); for t in "${TOPICS[@]}"
do
    # Using pre-encoded queries, full index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-cos-dpr-distil -topics ${t}-cos-dpr-distil -output run.${t}.cos-dpr-distil-full-pre.txt -threads 16 -efSearch 1000
    # Using pre-encoded queries, quantized index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-cos-dpr-distil-quantized -topics ${t}-cos-dpr-distil -output run.${t}.cos-dpr-distil-quantized-pre.txt -threads 16 -efSearch 1000
    # Using ONNX, full index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-cos-dpr-distil -topics ${t} -encoder CosDprDistil -output run.${t}.cos-dpr-distil-full-onnx.txt -threads 16 -efSearch 1000
    # Using ONNX, quantized index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-cos-dpr-distil-quantized -topics ${t} -encoder CosDprDistil -output run.${t}.cos-dpr-distil-quantized-onnx.txt -threads 16 -efSearch 1000
done

# BGE-base-en-v1.5
TOPICS=(msmarco-v1-passage-dev dl19-passage dl20-passage); for t in "${TOPICS[@]}"
do
    # Using pre-encoded queries, full index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-bge-base-en-v1.5 -topics ${t}-bge-base-en-v1.5 -output run.${t}.bge-base-en-v1.5-full-pre.txt -threads 16 -efSearch 1000
    # Using pre-encoded queries, quantized index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-bge-base-en-v1.5-quantized -topics ${t}-bge-base-en-v1.5 -output run.${t}.bge-base-en-v1.5-quantized-pre.txt -threads 16 -efSearch 1000
    # Using ONNX, full index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-bge-base-en-v1.5 -topics ${t} -encoder BgeBaseEn15 -output run.${t}.bge-base-en-v1.5-full-onnx.txt -threads 16 -efSearch 1000
    # Using ONNX, quantized index
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index msmarco-v1-passage-bge-base-en-v1.5-quantized -topics ${t} -encoder BgeBaseEn15 -output run.${t}.bge-base-en-v1.5-quantized-onnx.txt -threads 16 -efSearch 1000
done

Here are the expected scores (dev using MRR@10, DL19 and DL20 using nDCG@10):

dev DL19 DL20
BM25 0.1840 0.5058 0.4796
SPLADE++ ED (pre-encoded) 0.3830 0.7317 0.7198
SPLADE++ ED (ONNX) 0.3828 0.7308 0.7197
cos-DPR: full HNSW (pre-encoded) 0.3887 0.7250 0.7025
cos-DPR: quantized HNSW (pre-encoded) 0.3897 0.7240 0.7004
cos-DPR: full HNSW (ONNX) 0.3887 0.7250 0.7025
cos-DPR: quantized HNSW (ONNX) 0.3899 0.7247 0.6996
BGE-base-en-v1.5: full HNSW (pre-encoded) 0.3574 0.7065 0.6780
BGE-base-en-v1.5: quantized HNSW (pre-encoded) 0.3572 0.7016 0.6738
BGE-base-en-v1.5: full HNSW (ONNX) 0.3575 0.7016 0.6768
BGE-base-en-v1.5: quantized HNSW (ONNX) 0.3575 0.7017 0.6767

And here's the snippet of code to perform the evaluation (which will yield the results above):

wget https://raw.githubusercontent.com/castorini/anserini-tools/master/topics-and-qrels/qrels.msmarco-passage.dev-subset.txt
wget https://raw.githubusercontent.com/castorini/anserini-tools/master/topics-and-qrels/qrels.dl19-passage.txt
wget https://raw.githubusercontent.com/castorini/anserini-tools/master/topics-and-qrels/qrels.dl20-passage.txt

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.bm25.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.bm25.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.bm25.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.splade-pp-ed-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.splade-pp-ed-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.splade-pp-ed-pre.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.splade-pp-ed-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.splade-pp-ed-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.splade-pp-ed-onnx.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.cos-dpr-distil-full-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.cos-dpr-distil-full-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.cos-dpr-distil-full-pre.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.cos-dpr-distil-quantized-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.cos-dpr-distil-quantized-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.cos-dpr-distil-quantized-pre.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.cos-dpr-distil-full-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.cos-dpr-distil-full-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.cos-dpr-distil-full-onnx.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.cos-dpr-distil-quantized-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.cos-dpr-distil-quantized-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.cos-dpr-distil-quantized-onnx.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.bge-base-en-v1.5-full-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.bge-base-en-v1.5-full-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.bge-base-en-v1.5-full-pre.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.bge-base-en-v1.5-quantized-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.bge-base-en-v1.5-quantized-pre.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.bge-base-en-v1.5-quantized-pre.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.bge-base-en-v1.5-full-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.bge-base-en-v1.5-full-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.bge-base-en-v1.5-full-onnx.txt

echo ''

java -cp anserini-0.35.0-fatjar.jar trec_eval -c -M 10 -m recip_rank qrels.msmarco-passage.dev-subset.txt run.msmarco-v1-passage-dev.bge-base-en-v1.5-quantized-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl19-passage.txt                    run.dl19-passage.bge-base-en-v1.5-quantized-onnx.txt
java -cp anserini-0.35.0-fatjar.jar trec_eval -m ndcg_cut.10 -c qrels.dl20-passage.txt                    run.dl20-passage.bge-base-en-v1.5-quantized-onnx.txt

BEIR

Currently, Anserini provides support for the following models:

  • Flat = BM25, "flat" bag-of-words baseline
  • MF = BM25, "multifield" bag-of-words baseline
  • S = SPLADE++ EnsembleDistil:
    • Pre-encoded queries (Sp)
    • ONNX query encoding (So)
  • D = BGE-base-en-v1.5
    • Pre-encoded queries (Dp)
    • ONNX query encoding (Do)

The following snippet will generate the complete set of results for BEIR:

CORPORA=(trec-covid bioasq nfcorpus nq hotpotqa fiqa signal1m trec-news robust04 arguana webis-touche2020 cqadupstack-android cqadupstack-english cqadupstack-gaming cqadupstack-gis cqadupstack-mathematica cqadupstack-physics cqadupstack-programmers cqadupstack-stats cqadupstack-tex cqadupstack-unix cqadupstack-webmasters cqadupstack-wordpress quora dbpedia-entity scidocs fever climate-fever scifact); for c in "${CORPORA[@]}"
do
    # "flat" indexes
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index beir-v1.0.0-${c}.flat -topics beir-${c} -output run.beir.${c}.flat.txt -bm25 -removeQuery
    # "multifield" indexes
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index beir-v1.0.0-${c}.multifield -topics beir-${c} -output run.beir.${c}.multifield.txt -bm25 -removeQuery -fields contents=1.0 title=1.0
    # SPLADE++ ED, pre-encoded queries
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index beir-v1.0.0-${c}.splade-pp-ed -topics beir-${c}.splade-pp-ed -output run.beir.${c}.splade-pp-ed-pre.txt -impact -pretokenized -removeQuery
    # SPLADE++ ED, ONNX
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchCollection -index beir-v1.0.0-${c}.splade-pp-ed -topics beir-${c} -encoder SpladePlusPlusEnsembleDistil -output run.beir.${c}.splade-pp-ed-onnx.txt -impact -pretokenized -removeQuery
    # BGE-base-en-v1.5, pre-encoded queries
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index beir-v1.0.0-${c}.bge-base-en-v1.5 -topics beir-${c}.bge-base-en-v1.5 -output run.beir.${c}.bge-pre.txt -threads 16 -efSearch 1000 -removeQuery
    # BGE-base-en-v1.5, ONNX
    java -cp anserini-0.35.0-fatjar.jar io.anserini.search.SearchHnswDenseVectors -index beir-v1.0.0-${c}.bge-base-en-v1.5 -topics beir-${c} -encoder BgeBaseEn15 -output run.beir.${c}.bge-onnx.txt -threads 16 -efSearch 1000 -removeQuery
done

Here are the expected nDCG@10 scores:

Corpus Flat MF Sp So Dp Do
trec-covid 0.5947 0.6559 0.7274 0.7270 0.7834 0.7835
bioasq 0.5225 0.4646 0.4980 0.4980 0.4042 0.4042
nfcorpus 0.3218 0.3254 0.3470 0.3473 0.3735 0.3738
nq 0.3055 0.3285 0.5378 0.5372 0.5413 0.5415
hotpotqa 0.6330 0.6027 0.6868 0.6868 0.7242 0.7241
fiqa 0.2361 0.2361 0.3475 0.3473 0.4065 0.4065
signal1m 0.3304 0.3304 0.3008 0.3006 0.2869 0.2869
trec-news 0.3952 0.3977 0.4152 0.4169 0.4411 0.4410
robust04 0.4070 0.4070 0.4679 0.4651 0.4467 0.4437
arguana 0.3970 0.4142 0.5203 0.5218 0.6361 0.6228
webis-touche2020 0.4422 0.3673 0.2468 0.2464 0.2570 0.2571
cqadupstack-android 0.3801 0.3709 0.3904 0.3898 0.5075 0.5076
cqadupstack-english 0.3453 0.3321 0.4079 0.4078 0.4855 0.4855
cqadupstack-gaming 0.4822 0.4418 0.4957 0.4959 0.5965 0.5967
cqadupstack-gis 0.2901 0.2904 0.3150 0.3148 0.4129 0.4133
cqadupstack-mathematica 0.2015 0.2046 0.2377 0.2379 0.3163 0.3163
cqadupstack-physics 0.3214 0.3248 0.3599 0.3597 0.4722 0.4724
cqadupstack-programmers 0.2802 0.2963 0.3401 0.3399 0.4242 0.4238
cqadupstack-stats 0.2711 0.2790 0.2990 0.2980 0.3731 0.3728
cqadupstack-tex 0.2244 0.2086 0.2530 0.2529 0.3115 0.3115
cqadupstack-unix 0.2749 0.2788 0.3167 0.3170 0.4219 0.4220
cqadupstack-webmasters 0.3059 0.3008 0.3167 0.3166 0.4065 0.4072
cqadupstack-wordpress 0.2483 0.2562 0.2733 0.2718 0.3547 0.3547
quora 0.7886 0.7886 0.8343 0.8344 0.8890 0.8876
dbpedia-entity 0.3180 0.3128 0.4366 0.4374 0.4077 0.4076
scidocs 0.1490 0.1581 0.1591 0.1588 0.2170 0.2172
fever 0.6513 0.7530 0.7882 0.7879 0.8620 0.8620
climate-fever 0.1651 0.2129 0.2297 0.2298 0.3119 0.3117
scifact 0.6789 0.6647 0.7041 0.7036 0.7408 0.7408

And here's the snippet of code to perform the evaluation (which will yield the results above):

CORPORA=(trec-covid bioasq nfcorpus nq hotpotqa fiqa signal1m trec-news robust04 arguana webis-touche2020 cqadupstack-android cqadupstack-english cqadupstack-gaming cqadupstack-gis cqadupstack-mathematica cqadupstack-physics cqadupstack-programmers cqadupstack-stats cqadupstack-tex cqadupstack-unix cqadupstack-webmasters cqadupstack-wordpress quora dbpedia-entity scidocs fever climate-fever scifact); for c in "${CORPORA[@]}"
do
    wget https://raw.githubusercontent.com/castorini/anserini-tools/master/topics-and-qrels/qrels.beir-v1.0.0-${c}.test.txt
    echo $c
    java -cp anserini-0.35.0-fatjar.jar trec_eval -c -m ndcg_cut.10 qrels.beir-v1.0.0-${c}.test.txt run.beir.${c}.flat.txt
    java -cp anserini-0.35.0-fatjar.jar trec_eval -c -m ndcg_cut.10 qrels.beir-v1.0.0-${c}.test.txt run.beir.${c}.multifield.txt
    java -cp anserini-0.35.0-fatjar.jar trec_eval -c -m ndcg_cut.10 qrels.beir-v1.0.0-${c}.test.txt run.beir.${c}.splade-pp-ed-pre.txt
    java -cp anserini-0.35.0-fatjar.jar trec_eval -c -m ndcg_cut.10 qrels.beir-v1.0.0-${c}.test.txt run.beir.${c}.splade-pp-ed-onnx.txt
    java -cp anserini-0.35.0-fatjar.jar trec_eval -c -m ndcg_cut.10 qrels.beir-v1.0.0-${c}.test.txt run.beir.${c}.bge-pre.txt
    java -cp anserini-0.35.0-fatjar.jar trec_eval -c -m ndcg_cut.10 qrels.beir-v1.0.0-${c}.test.txt run.beir.${c}.bge-onnx.txt
done