regression.msmarco-v2-passage.splade-pp-ed.onnx.yaml Maven / Gradle / Ivy

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---
corpus: msmarco-v2-passage-splade-pp-ed
corpus_path: collections/msmarco/msmarco_v2_passage_splade_pp_ed/

download_url: https://rgw.cs.uwaterloo.ca/pyserini/data/msmarco_v2_passage_splade_pp_ed.tar
download_checksum: 2cdb2adc259b8fa6caf666b20ebdc0e8
download_corpus: msmarco_v2_passage_splade_pp_ed

index_path: indexes/lucene-inverted.msmarco-v2-passage.splade-pp-ed/
collection_class: JsonVectorCollection
generator_class: DefaultLuceneDocumentGenerator
index_threads: 24
index_options: -impact -pretokenized -storeRaw
index_stats:
  documents: 138364198
  documents (non-empty): 138364198
  total terms: 861058871141

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 Passage: Dev](https://microsoft.github.io/msmarco/TREC-Deep-Learning.html)"
    id: dev
    path: topics.msmarco-v2-passage.dev.txt
    qrel: qrels.msmarco-v2-passage.dev.txt
  - name: "[MS MARCO V2 Passage: Dev2](https://microsoft.github.io/msmarco/TREC-Deep-Learning.html)"
    id: dev2
    path: topics.msmarco-v2-passage.dev2.txt
    qrel: qrels.msmarco-v2-passage.dev2.txt

models:
  - name: splade-pp-ed-onnx
    display: SPLADE++ CoCondenser-EnsembleDistil
    params: -parallelism 16 -impact -pretokenized -encoder SpladePlusPlusEnsembleDistil
    results:
      MAP@100:
        - 0.1545
        - 0.1648
      MRR@100:
        - 0.1558
        - 0.1662
      R@100:
        - 0.6020
        - 0.6140
      R@1000:
        - 0.8223
        - 0.8129