|
conditions: |
|
- name: bm25-rocchio-d2q-t5-tuned |
|
display: BM25+Rocchio w/ doc2query-T5 (k1=2.18, b=0.86) |
|
display-html: BM25+Rocchio w/ doc2query-T5 (<i>k<sub><small>1</small></sub></i>=2.18, <i>b</i>=0.86) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-d2q-t5-docvectors --topics $topics --output $output --bm25 --rocchio |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.2395 |
|
R@1K: 0.9535 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4339 |
|
nDCG@10: 0.6559 |
|
R@1K: 0.8465 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4376 |
|
nDCG@10: 0.6224 |
|
R@1K: 0.8641 |
|
- name: bm25-rocchio-d2q-t5-default |
|
display: BM25+Rocchio w/ doc2query-T5 (k1=0.9, b=0.4) |
|
display-html: BM25+Rocchio w/ doc2query-T5 (<i>k<sub><small>1</small></sub></i>=0.9, <i>b</i>=0.4) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-d2q-t5-docvectors --topics $topics --output $output --bm25 --rocchio --k1 0.9 --b 0.4 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.2158 |
|
R@1K: 0.9467 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4469 |
|
nDCG@10: 0.6538 |
|
R@1K: 0.8855 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4246 |
|
nDCG@10: 0.6102 |
|
R@1K: 0.8675 |
|
- name: bm25-rocchio-default |
|
display: BM25+Rocchio (k1=0.9, b=0.4) |
|
display-html: BM25+Rocchio (<i>k<sub><small>1</small></sub></i>=0.9, <i>b</i>=0.4) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage --topics $topics --output $output --bm25 --k1 0.9 --b 0.4 --rocchio |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.1595 |
|
R@1K: 0.8620 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3474 |
|
nDCG@10: 0.5275 |
|
R@1K: 0.8007 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.3115 |
|
nDCG@10: 0.4910 |
|
R@1K: 0.8156 |
|
- name: bm25-rocchio-tuned |
|
display: BM25+Rocchio (k1=0.82, b=0.68) |
|
display-html: BM25+Rocchio (<i>k<sub><small>1</small></sub></i>=0.82, <i>b</i>=0.68) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage --topics $topics --output $output --bm25 --rocchio |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.1684 |
|
R@1K: 0.8726 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3396 |
|
nDCG@10: 0.5275 |
|
R@1K: 0.7948 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.3120 |
|
nDCG@10: 0.4908 |
|
R@1K: 0.8327 |
|
- name: distilbert-kd-tasb-pytorch |
|
display: "DistilBERT KD TASB: query inference with PyTorch" |
|
display-html: "DistilBERT KD TASB: query inference with PyTorch" |
|
display-row: "[5]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.distilbert-dot-tas_b-b256 --topics $topics --encoder sebastian-hofstaetter/distilbert-dot-tas_b-b256-msmarco --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3444 |
|
R@1K: 0.9771 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4590 |
|
nDCG@10: 0.7210 |
|
R@1K: 0.8406 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4698 |
|
nDCG@10: 0.6854 |
|
R@1K: 0.8727 |
|
- name: distilbert-kd-tasb |
|
display: "DistilBERT KD TASB: pre-encoded" |
|
display-html: "DistilBERT KD TASB: pre-encoded queries" |
|
display-row: "[5]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.distilbert-dot-tas_b-b256 --topics $topics --encoded-queries distilbert_tas_b-$topics --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3444 |
|
R@1K: 0.9771 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4590 |
|
nDCG@10: 0.7210 |
|
R@1K: 0.8406 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4698 |
|
nDCG@10: 0.6854 |
|
R@1K: 0.8727 |
|
- name: distilbert-kd-pytorch |
|
display: "DistilBERT KD: query inference with PyTorch" |
|
display-html: "DistilBERT KD: query inference with PyTorch" |
|
display-row: "[4]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.distilbert-dot-margin-mse-t2 --topics $topics --encoder sebastian-hofstaetter/distilbert-dot-margin_mse-T2-msmarco --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3251 |
|
R@1K: 0.9553 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4053 |
|
nDCG@10: 0.6994 |
|
R@1K: 0.7653 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4159 |
|
nDCG@10: 0.6447 |
|
R@1K: 0.7953 |
|
- name: distilbert-kd |
|
display: "DistilBERT KD: pre-encoded" |
|
display-html: "DistilBERT KD: pre-encoded queries" |
|
display-row: "[4]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.distilbert-dot-margin-mse-t2 --topics $topics --encoded-queries distilbert_kd-$topics --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3251 |
|
R@1K: 0.9553 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4053 |
|
nDCG@10: 0.6994 |
|
R@1K: 0.7653 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4159 |
|
nDCG@10: 0.6447 |
|
R@1K: 0.7953 |
|
- name: ance-pytorch |
|
display: "ANCE: query inference with PyTorch" |
|
display-html: "ANCE: query inference with PyTorch" |
|
display-row: "[3]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.ance --topics $topics --encoder castorini/ance-msmarco-passage --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3302 |
|
R@1K: 0.9587 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3710 |
|
nDCG@10: 0.6452 |
|
R@1K: 0.7554 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4076 |
|
nDCG@10: 0.6458 |
|
R@1K: 0.7764 |
|
- name: ance |
|
display: "ANCE: pre-encoded" |
|
display-html: "ANCE: pre-encoded queries" |
|
display-row: "[3]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.ance --topics $topics --encoded-queries ance-$topics --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3302 |
|
R@1K: 0.9584 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3710 |
|
nDCG@10: 0.6452 |
|
R@1K: 0.7554 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4076 |
|
nDCG@10: 0.6458 |
|
R@1K: 0.7764 |
|
- name: bm25-tuned |
|
display: BM25 (k1=0.82, b=0.68) |
|
display-html: BM25 (<i>k<sub><small>1</small></sub></i>=0.82, <i>b</i>=0.68) |
|
command: python -m pyserini.search.lucene --topics $topics --index msmarco-v1-passage --output $output --bm25 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.1875 |
|
R@1K: 0.8573 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.2903 |
|
nDCG@10: 0.4973 |
|
R@1K: 0.7450 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.2876 |
|
nDCG@10: 0.4876 |
|
R@1K: 0.8031 |
|
- name: bm25-rm3-tuned |
|
display: BM25+RM3 (k1=0.82, b=0.68) |
|
display-html: BM25+RM3 (<i>k<sub><small>1</small></sub></i>=0.82, <i>b</i>=0.68) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage --topics $topics --output $output --bm25 --rm3 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.1646 |
|
R@1K: 0.8704 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3339 |
|
nDCG@10: 0.5147 |
|
R@1K: 0.7950 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.3017 |
|
nDCG@10: 0.4924 |
|
R@1K: 0.8292 |
|
- name: bm25-default |
|
display: BM25 (k1=0.9, b=0.4) |
|
display-html: BM25 (<i>k<sub><small>1</small></sub></i>=0.9, <i>b</i>=0.4) |
|
display-row: "[<a href=\"#\" data-mdb-toggle=\"tooltip\" title=\"Ma et al. (SIGIR 2021) Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.\">1</a>] — (1a)" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage --topics $topics --output $output --bm25 --k1 0.9 --b 0.4 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.1840 |
|
R@1K: 0.8526 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3013 |
|
nDCG@10: 0.5058 |
|
R@1K: 0.7501 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.2856 |
|
nDCG@10: 0.4796 |
|
R@1K: 0.7863 |
|
- name: bm25-rm3-default |
|
display: BM25+RM3 (k1=0.9, b=0.4) |
|
display-html: BM25+RM3 (<i>k<sub><small>1</small></sub></i>=0.9, <i>b</i>=0.4) |
|
display-row: "[<a href=\"#\" data-mdb-toggle=\"tooltip\" title=\"Ma et al. (SIGIR 2021) Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.\">1</a>] — (1b)" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage --topics $topics --output $output --bm25 --k1 0.9 --b 0.4 --rm3 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.1566 |
|
R@1K: 0.8606 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.3416 |
|
nDCG@10: 0.5216 |
|
R@1K: 0.8136 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.3006 |
|
nDCG@10: 0.4896 |
|
R@1K: 0.8236 |
|
- name: bm25-d2q-t5-tuned |
|
display: BM25 w/ doc2query-T5 (k1=2.18, b=0.86) |
|
display-html: BM25 w/ doc2query-T5 (<i>k<sub><small>1</small></sub></i>=2.18, <i>b</i>=0.86) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-d2q-t5 --topics $topics --output $output --bm25 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.2816 |
|
R@1K: 0.9506 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4046 |
|
nDCG@10: 0.6336 |
|
R@1K: 0.8134 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4171 |
|
nDCG@10: 0.6265 |
|
R@1K: 0.8393 |
|
- name: bm25-d2q-t5-default |
|
display: BM25 w/ doc2query-T5 (k1=0.9, b=0.4) |
|
display-html: BM25 w/ doc2query-T5 (<i>k<sub><small>1</small></sub></i>=0.9, <i>b</i>=0.4) |
|
display-row: "[<a href=\"#\" data-mdb-toggle=\"tooltip\" title=\"Ma et al. (SIGIR 2021) Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.\">1</a>] — (2a)" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-d2q-t5 --topics $topics --output $output --bm25 --k1 0.9 --b 0.4 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.2723 |
|
R@1K: 0.9470 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4034 |
|
nDCG@10: 0.6417 |
|
R@1K: 0.8310 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4074 |
|
nDCG@10: 0.6187 |
|
R@1K: 0.8452 |
|
- name: bm25-rm3-d2q-t5-tuned |
|
display: BM25+RM3 w/ doc2query-T5 (k1=2.18, b=0.86) |
|
display-html: BM25+RM3 w/ doc2query-T5 (<i>k<sub><small>1</small></sub></i>=2.18, <i>b</i>=0.86) |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-d2q-t5-docvectors --topics $topics --output $output --bm25 --rm3 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.2382 |
|
R@1K: 0.9528 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4377 |
|
nDCG@10: 0.6537 |
|
R@1K: 0.8443 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4348 |
|
nDCG@10: 0.6235 |
|
R@1K: 0.8605 |
|
- name: bm25-rm3-d2q-t5-default |
|
display: BM25+RM3 w/ doc2query-T5 (k1=0.9, b=0.4) |
|
display-html: BM25+RM3 w/ doc2query-T5 (<i>k<sub><small>1</small></sub></i>=0.9, <i>b</i>=0.4) |
|
display-row: "[<a href=\"#\" data-mdb-toggle=\"tooltip\" title=\"Ma et al. (SIGIR 2021) Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.\">1</a>] — (2b)" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-d2q-t5-docvectors --topics $topics --output $output --bm25 --rm3 --k1 0.9 --b 0.4 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.2139 |
|
R@1K: 0.9460 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4483 |
|
nDCG@10: 0.6586 |
|
R@1K: 0.8863 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4286 |
|
nDCG@10: 0.6131 |
|
R@1K: 0.8700 |
|
- name: unicoil-pytorch |
|
display: "uniCOIL (w/ doc2query-T5): query inference with PyTorch" |
|
display-html: "uniCOIL (w/ doc2query-T5): query inference with PyTorch" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-unicoil --topics $topics --encoder castorini/unicoil-msmarco-passage --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3509 |
|
R@1K: 0.9581 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4617 |
|
nDCG@10: 0.7027 |
|
R@1K: 0.8291 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4429 |
|
nDCG@10: 0.6745 |
|
R@1K: 0.8433 |
|
- name: unicoil-onnx |
|
display: "uniCOIL (w/ doc2query-T5): query inference with ONNX" |
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display-html: "uniCOIL (w/ doc2query-T5): query inference with ONNX" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-unicoil --topics $topics --onnx-encoder UniCoil --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3509 |
|
R@1K: 0.9581 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4617 |
|
nDCG@10: 0.7027 |
|
R@1K: 0.8291 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4429 |
|
nDCG@10: 0.6745 |
|
R@1K: 0.8433 |
|
- name: unicoil |
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display: "uniCOIL (w/ doc2query-T5): pre-encoded" |
|
display-html: "uniCOIL (w/ doc2query-T5): pre-encoded queries" |
|
display-row: "[<a href=\"#\" data-mdb-toggle=\"tooltip\" title=\"Ma et al. (SIGIR 2021) Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.\">1</a>] — (3b)" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-unicoil --topics $topics --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset-unicoil |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3516 |
|
R@1K: 0.9582 |
|
- topic_key: dl19-passage-unicoil |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4612 |
|
nDCG@10: 0.7024 |
|
R@1K: 0.8292 |
|
- topic_key: dl20-unicoil |
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eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4430 |
|
nDCG@10: 0.6745 |
|
R@1K: 0.8430 |
|
- name: unicoil-noexp-pytorch |
|
display: "uniCOIL (noexp): query inference with PyTorch" |
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display-html: "uniCOIL (noexp): query inference with PyTorch" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-unicoil-noexp --topics $topics --encoder castorini/unicoil-noexp-msmarco-passage --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3153 |
|
R@1K: 0.9239 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4033 |
|
nDCG@10: 0.6434 |
|
R@1K: 0.7752 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4022 |
|
nDCG@10: 0.6524 |
|
R@1K: 0.7861 |
|
- name: unicoil-noexp-onnx |
|
display: "uniCOIL (noexp): query inference with ONNX" |
|
display-html: "uniCOIL (noexp): query inference with ONNX" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-unicoil-noexp --topics $topics --onnx-encoder UniCoil --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3119 |
|
R@1K: 0.9239 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4061 |
|
nDCG@10: 0.6531 |
|
R@1K: 0.7809 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.3909 |
|
nDCG@10: 0.6388 |
|
R@1K: 0.7915 |
|
- name: unicoil-noexp |
|
display: "uniCOIL (noexp): pre-encoded" |
|
display-html: "uniCOIL (noexp): pre-encoded queries" |
|
display-row: "[<a href=\"#\" data-mdb-toggle=\"tooltip\" title=\"Ma et al. (SIGIR 2021) Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.\">1</a>] — (3a)" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-unicoil-noexp --topics $topics --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset-unicoil-noexp |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3153 |
|
R@1K: 0.9239 |
|
- topic_key: dl19-passage-unicoil-noexp |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4033 |
|
nDCG@10: 0.6433 |
|
R@1K: 0.7752 |
|
- topic_key: dl20-unicoil-noexp |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4021 |
|
nDCG@10: 0.6523 |
|
R@1K: 0.7861 |
|
- name: splade-pp-ed-onnx |
|
display: "SPLADE++ EnsembleDistil: query inference with ONNX" |
|
display-html: "SPLADE++ EnsembleDistil: query inference with ONNX" |
|
display-row: "[2]" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-splade-pp-ed --topics $topics --onnx-encoder SpladePlusPlusEnsembleDistil --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3830 |
|
R@1K: 0.9831 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.5054 |
|
nDCG@10: 0.7320 |
|
R@1K: 0.8724 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.5002 |
|
nDCG@10: 0.7198 |
|
R@1K: 0.8995 |
|
- name: splade-pp-sd-onnx |
|
display: "SPLADE++ SelfDistil: query inference with ONNX" |
|
display-html: "SPLADE++ SelfDistil: query inference with ONNX" |
|
display-row: "[2]" |
|
command: python -m pyserini.search.lucene --threads 16 --batch-size 128 --index msmarco-v1-passage-splade-pp-sd --topics $topics --onnx-encoder SpladePlusPlusSelfDistil --output $output --hits 1000 --impact |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3778 |
|
R@1K: 0.9846 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4997 |
|
nDCG@10: 0.7356 |
|
R@1K: 0.8758 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.5140 |
|
nDCG@10: 0.7285 |
|
R@1K: 0.9023 |
|
- name: tct_colbert-v2-hnp-pytorch |
|
display: "TCT_ColBERT-V2-HN+: query inference with PyTorch" |
|
display-html: "TCT_ColBERT-V2-HN+: query inference with PyTorch" |
|
display-row: "[6]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.tct_colbert-v2-hnp --topics $topics --encoder castorini/tct_colbert-v2-hnp-msmarco --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3584 |
|
R@1K: 0.9695 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4469 |
|
nDCG@10: 0.7204 |
|
R@1K: 0.8261 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4754 |
|
nDCG@10: 0.6882 |
|
R@1K: 0.8429 |
|
- name: tct_colbert-v2-hnp |
|
display: "TCT_ColBERT-V2-HN+: pre-encoded" |
|
display-html: "TCT_ColBERT-V2-HN+: pre-encoded queries" |
|
display-row: "[6]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.tct_colbert-v2-hnp --topics $topics --encoded-queries tct_colbert-v2-hnp-$topics --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3584 |
|
R@1K: 0.9695 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4469 |
|
nDCG@10: 0.7204 |
|
R@1K: 0.8261 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4754 |
|
nDCG@10: 0.6882 |
|
R@1K: 0.8429 |
|
- name: slimr |
|
display: "SLIM: query inference with PyTorch" |
|
display-html: "SLIM: query inference with PyTorch" |
|
display-row: "[7]" |
|
command: python -m pyserini.search.lucene --threads 16 --batch 128 --index msmarco-v1-passage-slimr --topics $topics --encoder castorini/slimr-msmarco-passage --encoded-corpus scipy-sparse-vectors.msmarco-v1-passage-slimr --output $output --output-format msmarco --hits 1000 --impact --min-idf 3 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3581 |
|
R@1K: 0.9620 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4509 |
|
nDCG@10: 0.7010 |
|
R@1K: 0.8241 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4419 |
|
nDCG@10: 0.6403 |
|
R@1K: 0.8543 |
|
- name: slimr-pp |
|
display: "SLIM++: query inference with PyTorch" |
|
display-html: "SLIM++: query inference with PyTorch" |
|
display-row: "[7]" |
|
command: python -m pyserini.search.lucene --threads 16 --batch 128 --index msmarco-v1-passage-slimr-pp --topics $topics --encoder castorini/slimr-pp-msmarco-passage --encoded-corpus scipy-sparse-vectors.msmarco-v1-passage-slimr-pp --output $output --output-format msmarco --hits 1000 --impact --min-idf 3 |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.4032 |
|
R@1K: 0.9680 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4687 |
|
nDCG@10: 0.7140 |
|
R@1K: 0.8415 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4906 |
|
nDCG@10: 0.7021 |
|
R@1K: 0.8551 |
|
- name: aggretriever-distilbert-pytorch |
|
display: "Aggretriever-DistilBERT: query inference with PyTorch" |
|
display-html: "Aggretriever-DistilBERT: query inference with PyTorch" |
|
display-row: "[8]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.aggretriever-distilbert --topics $topics --encoder castorini/aggretriever-distilbert --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3412 |
|
R@1K: 0.9604 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4301 |
|
nDCG@10: 0.6816 |
|
R@1K: 0.8023 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4329 |
|
nDCG@10: 0.6726 |
|
R@1K: 0.8351 |
|
- name: aggretriever-cocondenser-pytorch |
|
display: "Aggretriever-coCondenser: query inference with PyTorch" |
|
display-html: "Aggretriever-coCondenser: query inference with PyTorch" |
|
display-row: "[8]" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 512 --index msmarco-v1-passage.aggretriever-cocondenser --topics $topics --encoder castorini/aggretriever-cocondenser --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3619 |
|
R@1K: 0.9735 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4350 |
|
nDCG@10: 0.6837 |
|
R@1K: 0.8078 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4710 |
|
nDCG@10: 0.6972 |
|
R@1K: 0.8555 |
|
- name: openai-ada2 |
|
display: "OpenAI ada2: pre-encoded queries" |
|
display-html: "OpenAI ada2: pre-encoded queries" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 128 --index msmarco-v1-passage.openai-ada2 --topics $topics --encoded-queries openai-ada2-$topics --output $output |
|
topics: |
|
- topic_key: msmarco-passage-dev-subset |
|
eval_key: msmarco-passage-dev-subset |
|
scores: |
|
- MRR@10: 0.3435 |
|
R@1K: 0.9858 |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.4788 |
|
nDCG@10: 0.7035 |
|
R@1K: 0.8629 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4771 |
|
nDCG@10: 0.6759 |
|
R@1K: 0.8705 |
|
- name: openai-ada2-hyde |
|
display: "HyDE-OpenAI ada2: pre-encoded queries" |
|
display-html: "HyDE-OpenAI ada2: pre-encoded queries" |
|
command: python -m pyserini.search.faiss --threads 16 --batch-size 128 --index msmarco-v1-passage.openai-ada2 --topics $topics --encoded-queries openai-ada2-$topics-hyde --output $output |
|
topics: |
|
- topic_key: dl19-passage |
|
eval_key: dl19-passage |
|
scores: |
|
- MAP: 0.5125 |
|
nDCG@10: 0.7163 |
|
R@1K: 0.9002 |
|
- topic_key: dl20 |
|
eval_key: dl20-passage |
|
scores: |
|
- MAP: 0.4938 |
|
nDCG@10: 0.6666 |
|
R@1K: 0.8919 |