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Adds baselines for rag24.test with umbrela qrel
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src/main/resources/docgen/templates/rag24-doc-segmented-test.template
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# Anserini Regressions: TREC 2024 RAG Track Test Topics | ||
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**Models**: various bag-of-words approaches on segmented documents | ||
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This page describes experiments, integrated into Anserini's regression testing framework, on the "RAGgy dev topics" on the MS MARCO V2.1 _segmented_ document corpus. | ||
This corpus was derived from the MS MARCO V2 _segmented_ document corpus and prepared for the TREC 2024 RAG Track. | ||
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Here, we cover bag-of-words baselines where each _segment_ in the MS MARCO V2.1 segmented document corpus is treated as a unit of indexing. | ||
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The exact configurations for these regressions are stored in [this YAML file](${yaml}). | ||
Note that this page is automatically generated from [this template](${template}) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead. | ||
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From one of our Waterloo servers (e.g., `orca`), the following command will perform the complete regression, end to end: | ||
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``` | ||
python src/main/python/run_regression.py --index --verify --search --regression ${test_name} | ||
``` | ||
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## Indexing | ||
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Typical indexing command: | ||
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``` | ||
${index_cmds} | ||
``` | ||
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The setting of `-input` should be a directory containing the compressed `jsonl` files that comprise the corpus. | ||
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For additional details, see explanation of [common indexing options](${root_path}/docs/common-indexing-options.md). | ||
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## Retrieval | ||
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Topics and qrels are stored [here](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels), which is linked to the Anserini repo as a submodule. | ||
These evaluation resources are from the original V2 corpus, but have been "projected" over to the V2.1 corpus. | ||
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After indexing has completed, you should be able to perform retrieval as follows: | ||
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``` | ||
${ranking_cmds} | ||
``` | ||
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Evaluation can be performed using `trec_eval`: | ||
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``` | ||
${eval_cmds} | ||
``` | ||
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## Effectiveness | ||
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With the above commands, you should be able to reproduce the following results: | ||
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${effectiveness} |
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src/main/resources/regression/rag24-doc-segmented-test.yaml
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--- | ||
corpus: msmarco-v2.1-doc-segmented | ||
corpus_path: collections/msmarco/msmarco_v2.1_doc_segmented/ | ||
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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 | ||
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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 | ||
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topic_reader: TsvInt | ||
topics: | ||
- name: "RAG 24: Test queries" | ||
id: rag24.test | ||
path: topics.rag24.test.txt | ||
qrel: qrels.rag24.test-umbrela-all.txt | ||
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models: | ||
- name: bm25-default | ||
display: BM25 (default) | ||
params: -bm25 | ||
results: | ||
MAP@100: | ||
- 0.0861 | ||
MRR@100: | ||
- 0.7010 | ||
nDCG@10: | ||
- 0.3290 | ||
R@100: | ||
- 0.1395 | ||
R@1000: | ||
- 0.3467 | ||
- name: bm25-default+rm3 | ||
display: +RM3 | ||
params: -bm25 -rm3 -collection MsMarcoV2DocCollection | ||
results: | ||
MAP@100: | ||
- 0.0873 | ||
MRR@100: | ||
- 0.6687 | ||
nDCG@10: | ||
- 0.3256 | ||
R@100: | ||
- 0.1318 | ||
R@1000: | ||
- 0.3521 | ||
- name: bm25-default+rocchio | ||
display: +Rocchio | ||
params: -bm25 -rocchio -collection MsMarcoV2DocCollection | ||
results: | ||
MAP@100: | ||
- 0.0929 | ||
MRR@100: | ||
- 0.6791 | ||
nDCG@10: | ||
- 0.3307 | ||
R@100: | ||
- 0.1384 | ||
R@1000: | ||
- 0.3667 |