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dl23-doc-segmented-msmarco-v2.1.yaml
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dl23-doc-segmented-msmarco-v2.1.yaml
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---
corpus: msmarco-v2.1-doc-segmented
corpus_path: collections/msmarco/msmarco_v2.1_doc_segmented/
index_path: indexes/lucene-inverted.msmarco-v2.1-doc-segmented/
collection_class: MsMarcoV2DocCollection
generator_class: DefaultLuceneDocumentGenerator
index_threads: 24
index_options: -storeRaw
index_stats:
documents: 113520750
documents (non-empty): 113520750
total terms: 22707699649
metrics:
- metric: MAP@100
command: bin/trec_eval
params: -c -M 100 -m map
separator: "\t"
parse_index: 2
metric_precision: 4
can_combine: no
- metric: MRR@100
command: bin/trec_eval
params: -c -M 100 -m recip_rank
separator: "\t"
parse_index: 2
metric_precision: 4
can_combine: true
- metric: nDCG@10
command: bin/trec_eval
params: -c -m ndcg_cut.10
separator: "\t"
parse_index: 2
metric_precision: 4
can_combine: true
- metric: R@100
command: bin/trec_eval
params: -c -m recall.100
separator: "\t"
parse_index: 2
metric_precision: 4
can_combine: false
- metric: R@1000
command: bin/trec_eval
params: -c -m recall.1000
separator: "\t"
parse_index: 2
metric_precision: 4
can_combine: false
topic_reader: TsvInt
topics:
- name: "[DL23 (Doc)](https://microsoft.github.io/msmarco/TREC-Deep-Learning)"
id: dl23
path: topics.dl23.txt
qrel: qrels.dl23-doc-msmarco-v2.1.txt
models:
- name: bm25-default
display: BM25 (default)
params: -bm25 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000
results:
MAP@100:
- 0.1391
MRR@100:
- 0.6519
nDCG@10:
- 0.3356
R@100:
- 0.3049
R@1000:
- 0.5852
- name: bm25-default+rm3
display: +RM3
params: -bm25 -rm3 -collection MsMarcoV2DocCollection -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000
results:
MAP@100:
- 0.1716
MRR@100:
- 0.6277
nDCG@10:
- 0.3435
R@100:
- 0.3255
R@1000:
- 0.5895
- name: bm25-default+rocchio
display: +Rocchio
params: -bm25 -rocchio -collection MsMarcoV2DocCollection -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000
results:
MAP@100:
- 0.1722
MRR@100:
- 0.6202
nDCG@10:
- 0.3464
R@100:
- 0.3340
R@1000:
- 0.6014