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Adds baselines for rag24.test with umbrela qrel #2630
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101 changes: 101 additions & 0 deletions
101
docs/regressions/regressions-rag24-doc-segmented-test.md
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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 | ||
|
|
||
| This page describes regression experiments for document ranking _on the segmented version_ of the MS MARCO V2.1 document corpus using the test queries, which is integrated into Anserini's regression testing framework. | ||
| 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](../../src/main/resources/regression/rag24-doc-segmented-test.yaml). | ||
| Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/rag24-doc-segmented-test.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 rag24-doc-segmented-test | ||
| ``` | ||
|
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| ## Indexing | ||
|
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| Typical indexing command: | ||
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| ``` | ||
| bin/run.sh io.anserini.index.IndexCollection \ | ||
| -threads 24 \ | ||
| -collection MsMarcoV2DocCollection \ | ||
| -input /path/to/msmarco-v2.1-doc-segmented \ | ||
| -generator DefaultLuceneDocumentGenerator \ | ||
| -index indexes/lucene-inverted.msmarco-v2.1-doc-segmented/ \ | ||
| -storeRaw \ | ||
| >& logs/log.msmarco-v2.1-doc-segmented & | ||
| ``` | ||
|
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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](../../docs/common-indexing-options.md). | ||
|
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| ## Retrieval | ||
|
|
||
| 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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| ``` | ||
| bin/run.sh io.anserini.search.SearchCollection \ | ||
| -index indexes/lucene-inverted.msmarco-v2.1-doc-segmented/ \ | ||
| -topics tools/topics-and-qrels/topics.rag24.test.txt \ | ||
| -topicReader TsvInt \ | ||
| -output runs/run.msmarco-v2.1-doc-segmented.bm25-default.topics.rag24.test.txt \ | ||
| -bm25 & | ||
|
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| bin/run.sh io.anserini.search.SearchCollection \ | ||
| -index indexes/lucene-inverted.msmarco-v2.1-doc-segmented/ \ | ||
| -topics tools/topics-and-qrels/topics.rag24.test.txt \ | ||
| -topicReader TsvInt \ | ||
| -output runs/run.msmarco-v2.1-doc-segmented.bm25-default+rm3.topics.rag24.test.txt \ | ||
| -bm25 -rm3 -collection MsMarcoV2DocCollection & | ||
|
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| bin/run.sh io.anserini.search.SearchCollection \ | ||
| -index indexes/lucene-inverted.msmarco-v2.1-doc-segmented/ \ | ||
| -topics tools/topics-and-qrels/topics.rag24.test.txt \ | ||
| -topicReader TsvInt \ | ||
| -output runs/run.msmarco-v2.1-doc-segmented.bm25-default+rocchio.topics.rag24.test.txt \ | ||
| -bm25 -rocchio -collection MsMarcoV2DocCollection & | ||
| ``` | ||
|
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| Evaluation can be performed using `trec_eval`: | ||
|
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| ``` | ||
| bin/trec_eval -c -M 100 -m map tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default.topics.rag24.test.txt | ||
| bin/trec_eval -c -m recall.100 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default.topics.rag24.test.txt | ||
| bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default.topics.rag24.test.txt | ||
| bin/trec_eval -c -M 100 -m recip_rank -c -m ndcg_cut.10 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default.topics.rag24.test.txt | ||
|
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| bin/trec_eval -c -M 100 -m map tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rm3.topics.rag24.test.txt | ||
| bin/trec_eval -c -m recall.100 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rm3.topics.rag24.test.txt | ||
| bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rm3.topics.rag24.test.txt | ||
| bin/trec_eval -c -M 100 -m recip_rank -c -m ndcg_cut.10 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rm3.topics.rag24.test.txt | ||
|
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| bin/trec_eval -c -M 100 -m map tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rocchio.topics.rag24.test.txt | ||
| bin/trec_eval -c -m recall.100 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rocchio.topics.rag24.test.txt | ||
| bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rocchio.topics.rag24.test.txt | ||
| bin/trec_eval -c -M 100 -m recip_rank -c -m ndcg_cut.10 tools/topics-and-qrels/qrels.rag24.test-umbrela-all.txt runs/run.msmarco-v2.1-doc-segmented.bm25-default+rocchio.topics.rag24.test.txt | ||
| ``` | ||
|
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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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| | **MAP@100** | **BM25 (default)**| **+RM3** | **+Rocchio**| | ||
| |:-------------------------------------------------------------------------------------------------------------|-----------|-----------|-----------| | ||
| | RAG 24: Test queries | 0.0861 | 0.0873 | 0.0929 | | ||
| | **MRR@100** | **BM25 (default)**| **+RM3** | **+Rocchio**| | ||
| | RAG 24: Test queries | 0.7010 | 0.6687 | 0.6791 | | ||
| | **nDCG@10** | **BM25 (default)**| **+RM3** | **+Rocchio**| | ||
| | RAG 24: Test queries | 0.3290 | 0.3256 | 0.3307 | | ||
| | **R@100** | **BM25 (default)**| **+RM3** | **+Rocchio**| | ||
| | RAG 24: Test queries | 0.1395 | 0.1318 | 0.1384 | | ||
| | **R@1000** | **BM25 (default)**| **+RM3** | **+Rocchio**| | ||
| | RAG 24: Test queries | 0.3467 | 0.3521 | 0.3667 | |
52 changes: 52 additions & 0 deletions
52
src/main/resources/docgen/templates/rag24-doc-segmented-test.template
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,52 @@ | ||
| # Anserini Regressions: TREC 2024 RAG Track Test Topics | ||
|
|
||
| **Models**: various bag-of-words approaches on segmented documents | ||
|
|
||
| This page describes regression experiments for document ranking _on the segmented version_ of the MS MARCO V2.1 document corpus using the test queries, which is integrated into Anserini's regression testing framework. | ||
| This corpus was derived from the MS MARCO V2 _segmented_ document corpus and prepared for the TREC 2024 RAG Track. | ||
|
|
||
| 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. | ||
|
|
||
| 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. | ||
|
|
||
| From one of our Waterloo servers (e.g., `orca`), the following command will perform the complete regression, end to end: | ||
|
|
||
| ``` | ||
| python src/main/python/run_regression.py --index --verify --search --regression ${test_name} | ||
| ``` | ||
|
|
||
| ## Indexing | ||
|
|
||
| Typical indexing command: | ||
|
|
||
| ``` | ||
| ${index_cmds} | ||
| ``` | ||
|
|
||
| The setting of `-input` should be a directory containing the compressed `jsonl` files that comprise the corpus. | ||
|
|
||
| For additional details, see explanation of [common indexing options](${root_path}/docs/common-indexing-options.md). | ||
|
|
||
| ## Retrieval | ||
|
|
||
| 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. | ||
|
|
||
| After indexing has completed, you should be able to perform retrieval as follows: | ||
|
|
||
| ``` | ||
| ${ranking_cmds} | ||
| ``` | ||
|
|
||
| Evaluation can be performed using `trec_eval`: | ||
|
|
||
| ``` | ||
| ${eval_cmds} | ||
| ``` | ||
|
|
||
| ## Effectiveness | ||
|
|
||
| With the above commands, you should be able to reproduce the following results: | ||
|
|
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| ${effectiveness} |
101 changes: 101 additions & 0 deletions
101
src/main/resources/regression/rag24-doc-segmented-test.yaml
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|---|---|---|
| @@ -0,0 +1,101 @@ | ||
| --- | ||
| 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 | ||
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should we name
...test-umbrela-all?There was a problem hiding this comment.
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Overriding above; nope, this is fine.