regression.msmarco-v2-doc.yaml Maven / Gradle / Ivy
---
corpus: msmarco-v2-doc
corpus_path: collections/msmarco/msmarco_v2_doc/
index_path: indexes/lucene-inverted.msmarco-v2-doc/
collection_class: MsMarcoV2DocCollection
generator_class: DefaultLuceneDocumentGenerator
index_threads: 24
index_options: -storeRaw
index_stats:
documents: 11959635
documents (non-empty): 11959635
total terms: 14165667143
metrics:
- metric: MAP@100
command: bin/trec_eval
params: -c -M 100 -m map
separator: "\t"
parse_index: 2
metric_precision: 4
can_combine: true
- 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: 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: "[MS MARCO V2 Doc: Dev](https://microsoft.github.io/msmarco/TREC-Deep-Learning.html)"
id: dev
path: topics.msmarco-v2-doc.dev.txt
qrel: qrels.msmarco-v2-doc.dev.txt
- name: "[MS MARCO V2 Doc: Dev2](https://microsoft.github.io/msmarco/TREC-Deep-Learning.html)"
id: dev2
path: topics.msmarco-v2-doc.dev2.txt
qrel: qrels.msmarco-v2-doc.dev2.txt
models:
- name: bm25-default
display: BM25 (default)
params: -bm25
results:
MAP@100:
- 0.1552
- 0.1639
MRR@100:
- 0.1572
- 0.1659
R@100:
- 0.5956
- 0.5970
R@1000:
- 0.8054
- 0.8029
# PRF regressions are no longer maintained for sparse judgments to reduce running times.
# (commenting out instead of removing; in case these numbers are needed, just uncomment and rerun.)
#
# - name: bm25-default+rm3
# display: +RM3
# params: -bm25 -rm3 -collection MsMarcoV2DocCollection
# results:
# MAP@100:
# - 0.0965
# - 0.1016
# MRR@100:
# - 0.0974
# - 0.1033
# R@100:
# - 0.5108
# - 0.5253
# R@1000:
# - 0.7699
# - 0.7736
# - name: bm25-default+rocchio
# display: +Rocchio
# params: -bm25 -rocchio -collection MsMarcoV2DocCollection
# results:
# MAP@100:
# - 0.0965
# - 0.1037
# MRR@100:
# - 0.0974
# - 0.1052
# R@100:
# - 0.5135
# - 0.5261
# R@1000:
# - 0.7697
# - 0.7762
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