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1
- ---
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- license: apache-2.0
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- configs:
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- - config_name: agnews
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- data_files: "agnews.jsonl.tar.gz"
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- - config_name: AllNLI
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- data_files: "AllNLI.jsonl.tar.gz"
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- - config_name: altlex
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- data_files: "altlex.jsonl.tar.gz"
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- - config_name: amazon_review_2018_1m
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- data_files: "amazon_review_2018_1m.jsonl.tar.gz"
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- - config_name: cnn_dailymail
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- data_files: "cnn_dailymail.jsonl.tar.gz"
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- - config_name: codesearchnet
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- data_files: "codesearchnet.jsonl.tar.gz"
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- - config_name: dureader
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- data_files: "dureader.jsonl.tar.gz"
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- - config_name: eli5_question_answer
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- data_files: "eli5_question_answer.jsonl.tar.gz"
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- - config_name: gooaq_pairs
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- data_files: "gooaq_pairs.jsonl.tar.gz"
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- - config_name: hotpotqa
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- data_files: "hotpotqa.jsonl.tar.gz"
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- - config_name: medmcqa
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- data_files: "medmcqa.jsonl.tar.gz"
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- - config_name: miracl
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- data_files: "miracl.jsonl.tar.gz"
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- - config_name: mr_tydi_combined
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- data_files: "mr_tydi_combined.jsonl.tar.gz"
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- - config_name: msmarco
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- data_files: "msmarco.jsonl.tar.gz"
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- - config_name: nq
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- data_files: "nq.jsonl.tar.gz"
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- - config_name: quora_duplicates_triplets
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- data_files: "quora_duplicates_triplets.jsonl.tar.gz"
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- - config_name: searchQA_top5_snippets
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- data_files: "searchQA_top5_snippets.jsonl.tar.gz"
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- - config_name: sentence-compression
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- data_files: "sentence-compression.jsonl.tar.gz"
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- - config_name: SimpleWiki
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- data_files: "SimpleWiki.jsonl.tar.gz"
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- - config_name: squad_pairs
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- data_files: "squad_pairs.jsonl.tar.gz"
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- - config_name: stackexchange_duplicate_questions_title-body_title-body
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- data_files: "stackexchange_duplicate_questions_title-body_title-body.jsonl.tar.gz"
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- - config_name: t2ranking
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- data_files: "t2ranking.jsonl.tar.gz"
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- - config_name: trivia
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- data_files: "trivia.jsonl.tar.gz"
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- - config_name: xsum
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- data_files: "xsum.jsonl.tar.gz"
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- - config_name: yahoo_answers_title_answer
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- data_files: "yahoo_answers_title_answer.jsonl.tar.gz"
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- ---
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-
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- # tdro-llm/finetune_data
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-
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- [![arxiv](https://img.shields.io/badge/arXiv-2408.10613-b31b1b.svg)](https://arxiv.org/abs/2408.10613)
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- [![Github](https://img.shields.io/badge/GitHub-tdro-8A2BE2.svg)](https://github.com/tdro-llm/tdro)
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-
61
- [tDRO: Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval](https://arxiv.org/abs/2408.10613). Guangyuan Ma, Yongliang Ma, Xing Wu, Zhenpeng Su, Ming Zhou and Songlin Hu.
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-
63
- This repo contains all fine-tuning data for Large Language Model-based Dense Retrieval. Please refer to [this repo](https://github.com/tdro-llm/tdro) for details to reproduce.
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-
65
-
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- A total of 25 heterogeneous retrieval fine-tuning datasets with **Hard Negatives** and **Deduplication** (with test sets) are listed as belows.
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-
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- | **Dataset** | **Language** | **Category** | **Symmetry** | **Reference** | **Format** | **HN Mine** | **Size** | **Deduped Size** | **Duplicates** |
69
- |---------------------------------------------------------|--------------|------------------------------|--------------|---------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------|----------|------------------|----------------|
70
- | agnews | English | News | Asymmetric | [AG news corpus](http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html) | (Title, Description, Negatives) of news articles from the AG News dataset | bge-base-en-v1.5 mine | 1157745 | 1157745 | 0 |
71
- | AllNLI | English | NLI | Symmetric | [SNLI and MNLI](https://huggingface.co/datasets/multi_nli) | (Anchor, Entailment_Text, Contradiction_Text) - Combination of SNLI + MultiNLI Triplets | Sentence Transformers Train HN | 277230 | 277230 | 0 |
72
- | altlex | English | Wikipedia Pair | Symmetric | [altlex](https://github.com/chridey/altlex/) | (English_Wikipedia, Simple_English_Wikipedia, Negatives) - Matched pairs | bge-base-en-v1.5 mine | 112696 | 112696 | 0 |
73
- | amazon_review_2018_1m | English | Amazon | Asymmetric | [Amazon review data (2018)](http://deepyeti.ucsd.edu/jianmo/amazon/index.html) | (Title, review, Negatives) from Amazon. Only Top 1 million samples are used here to shrink the dataset sizes. | bge-base-en-v1.5 mine | 1000000 | 999999 | 1 |
74
- | cnn_dailymail | English | News | Asymmetric | [CNN Dailymail Dataset](https://huggingface.co/datasets/cnn_dailymail) | (highlight sentences, article) with all highlight sentences as one text for each news article | bge-base-en-v1.5 mine | 311971 | 311971 | 0 |
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- | codesearchnet | English | Github | Asymmetric | [CodeSearchNet](https://huggingface.co/datasets/code_search_net) | (Comment, Code, Negatives) - pairs from opensource libraries hosted on GitHub. It contains code and documentation for several programming languages. | bge-base-en-v1.5 mine | 1375067 | 1375067 | 0 |
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- | dureader | Chinese | Multilingual Web Collections | Asymmetric | [DuReader Retrieval](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval) | (Question, Answer, Negatives) | Use originally provided HN | 86395 | 86395 | 0 |
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- | eli5_question_answer | English | Reddit | Asymmetric | [ELI5](https://huggingface.co/datasets/eli5) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 325475 | 325390 | 85 |
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- | gooaq_pairs | English | Web Collections | Asymmetric | [GooAQ](https://github.com/allenai/gooaq) | (Question, Answer, Negatives) - Pairs from Google auto suggest | bge-base-en-v1.5 mine | 3012496 | 3012347 | 149 |
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- | hotpotqa | English | Wikipedia QA | Asymmetric | [HotpotQA](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/hotpotqa.zip) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 85000 | 85000 | 0 |
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- | medmcqa | English | Medical | Asymmetric | [MedMCQA](https://huggingface.co/datasets/openlifescienceai/medmcqa) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 160869 | 160865 | 4 |
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- | miracl | 16 languages | Multilingual Wikipedia | Asymmetric | [MIRACL](https://huggingface.co/datasets/miracl/miracl) | (Question, Answer, Negatives) | Use originally provided HN | 32561 | 32405 | 156 |
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- | mr_tydi_combined | 11 languages | Multilingual Wikipedia | Asymmetric | [Mr. TyDi](https://huggingface.co/datasets/castorini/mr-tydi) | (Question, Answer, Negatives) | Use originally provided HN | 48715 | 48475 | 240 |
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- | msmarco | English | Web Collections | Asymmetric | [MS MARCO Passages](https://github.com/microsoft/MSMARCO-Passage-Ranking) | (Question, Answer, Negatives) | bowdpr HN by following [this link](https://github.com/ma787639046/bowdpr) | 502939 | 502854 | 85 |
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- | nq | English | Wikipedia QA | Asymmetric | [NQ](https://github.com/facebookresearch/DPR) | (Question, Answer, Negatives) | bowdpr HN by following [this link](https://github.com/ma787639046/bowdpr) | 58812 | 58800 | 12 |
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- | quora_duplicates_triplets | English | Forum Duplicates | Symmetric | [QQP](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs) | (Question, Duplicated Question, Negatives) - Duplicate question pairs from Quora | Sentence Transformers Train HN | 101762 | 97011 | 4751 |
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- | searchQA_top5_snippets | English | Web Collections | Asymmetric | [search_qa](https://huggingface.co/datasets/search_qa) | (Question, Top5 text snippets, Negatives) from SearchQA dataset. | bge-base-en-v1.5 mine | 117220 | 117219 | 1 |
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- | sentence-compression | English | News | Asymmetric | [Sentence-Compression](https://github.com/google-research-datasets/sentence-compression) | (Long text, short text) about sentence-compression | bge-base-en-v1.5 mine | 180000 | 180000 | 0 |
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- | SimpleWiki | English | Wikipedia Pair | Symmetric | [SimpleWiki](https://cs.pomona.edu/~dkauchak/simplification/) | (English_Wikipedia, Simple_English_Wikipedia, Negatives) matched pairs | bge-base-en-v1.5 mine | 102225 | 102225 | 0 |
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- | squad_pairs | English | Wikipedia QA | Asymmetric | [SQuAD](https://huggingface.co/datasets/squad) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 87599 | 87595 | 4 |
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- | stackexchange_duplicate_questions_title-body_title-body | English | Forum Duplicates | Symmetric | [Stack Exchange Data API](https://data.stackexchange.com/apple/query/fork/1456963) | (Title-Body, Duplicated Title-Body, Negatives) - pairs of duplicate questions from StackExchange | bge-base-en-v1.5 mine | 250519 | 250516 | 3 |
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- | t2ranking | Chinese | Multilingual Web Collections | Asymmetric | [T2Ranking](https://github.com/THUIR/T2Ranking/) | (Question, Answer, Negatives) | Use originally provided HN | 200376 | 200376 | 0 |
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- | trivia | English | Wikipedia QA | Asymmetric | [Trivia QA](https://github.com/facebookresearch/DPR) | (Question, Answer, Negatives) | bowdpr HN by following [this link](https://github.com/ma787639046/bowdpr) | 60380 | 60370 | 10 |
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- | xsum | English | News | Asymmetric | [xsum](https://huggingface.co/datasets/xsum) | (Summary, News Article) pairs from XSUM dataset | bge-base-en-v1.5 mine | 226711 | 226711 | 0 |
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- | yahoo_answers_title_answer | English | Yahoo | Asymmetric | [Yahoo Answers](https://www.kaggle.com/soumikrakshit/yahoo-answers-dataset) | (Title, Answer, Negatives) | bge-base-en-v1.5 mine | 1198260 | 1198018 | 242 |
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- | **Total Lines** | | | | | | | 11073023 | 11067280 | 5743 |
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-
97
- ## Cite
98
- If you are interested in our work, please consider citing our paper.
99
-
100
- ```bibtex
101
- @article{ma2024tdro,
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- author = {Guangyuan Ma and
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- Yongliang Ma and
104
- Xing Wu and
105
- Zhenpeng Su and
106
- Ming Zhou and
107
- Songlin Hu},
108
- title = {Task-level Distributionally Robust Optimization for Large Language
109
- Model-based Dense Retrieval},
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- journal = {CoRR},
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- volume = {abs/2408.10613},
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- year = {2024},
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- url = {https://doi.org/10.48550/arXiv.2408.10613},
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- doi = {10.48550/ARXIV.2408.10613},
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- eprinttype = {arXiv},
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- eprint = {2408.10613},
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- timestamp = {Tue, 24 Sep 2024 17:36:32 +0200},
118
- }
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- ```
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-
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-
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-
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-
 
1
+ ---
2
+ license: apache-2.0
3
+ configs:
4
+ - config_name: agnews
5
+ data_files: "agnews.jsonl.tar.gz"
6
+ - config_name: AllNLI
7
+ data_files: "AllNLI.jsonl.tar.gz"
8
+ - config_name: altlex
9
+ data_files: "altlex.jsonl.tar.gz"
10
+ - config_name: amazon_review_2018_1m
11
+ data_files: "amazon_review_2018_1m.jsonl.tar.gz"
12
+ - config_name: cnn_dailymail
13
+ data_files: "cnn_dailymail.jsonl.tar.gz"
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+ - config_name: codesearchnet
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+ data_files: "codesearchnet.jsonl.tar.gz"
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+ - config_name: dureader
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+ data_files: "dureader.jsonl.tar.gz"
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+ - config_name: eli5_question_answer
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+ data_files: "eli5_question_answer.jsonl.tar.gz"
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+ - config_name: gooaq_pairs
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+ data_files: "gooaq_pairs.jsonl.tar.gz"
22
+ - config_name: hotpotqa
23
+ data_files: "hotpotqa.jsonl.tar.gz"
24
+ - config_name: medmcqa
25
+ data_files: "medmcqa.jsonl.tar.gz"
26
+ - config_name: miracl
27
+ data_files: "miracl.jsonl.tar.gz"
28
+ - config_name: mr_tydi_combined
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+ data_files: "mr_tydi_combined.jsonl.tar.gz"
30
+ - config_name: msmarco
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+ data_files: "msmarco.jsonl.tar.gz"
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+ - config_name: nq
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+ data_files: "nq.jsonl.tar.gz"
34
+ - config_name: quora_duplicates_triplets
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+ data_files: "quora_duplicates_triplets.jsonl.tar.gz"
36
+ - config_name: searchQA_top5_snippets
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+ data_files: "searchQA_top5_snippets.jsonl.tar.gz"
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+ - config_name: sentence-compression
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+ data_files: "sentence-compression.jsonl.tar.gz"
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+ - config_name: SimpleWiki
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+ data_files: "SimpleWiki.jsonl.tar.gz"
42
+ - config_name: squad_pairs
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+ data_files: "squad_pairs.jsonl.tar.gz"
44
+ - config_name: stackexchange_duplicate_questions_title-body_title-body
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+ data_files: "stackexchange_duplicate_questions_title-body_title-body.jsonl.tar.gz"
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+ - config_name: t2ranking
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+ data_files: "t2ranking.jsonl.tar.gz"
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+ - config_name: trivia
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+ data_files: "trivia.jsonl.tar.gz"
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+ - config_name: xsum
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+ data_files: "xsum.jsonl.tar.gz"
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+ - config_name: yahoo_answers_title_answer
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+ data_files: "yahoo_answers_title_answer.jsonl.tar.gz"
54
+ ---
55
+
56
+ # tdro-llm/finetune_data
57
+
58
+ [![arxiv](https://img.shields.io/badge/arXiv-2408.10613-b31b1b.svg)](https://arxiv.org/abs/2408.10613)
59
+ [![Github](https://img.shields.io/badge/GitHub-tdro-8A2BE2.svg)](https://github.com/ma787639046/tdro)
60
+
61
+ [tDRO: Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval](https://arxiv.org/abs/2408.10613). Guangyuan Ma, Yongliang Ma, Xing Wu, Zhenpeng Su, Ming Zhou and Songlin Hu.
62
+
63
+ This repo contains all fine-tuning data for Large Language Model-based Dense Retrieval. Please refer to [this repo](https://github.com/ma787639046/tdro) for details to reproduce.
64
+
65
+
66
+ A total of 25 heterogeneous retrieval fine-tuning datasets with **Hard Negatives** and **Deduplication** (with test sets) are listed as belows.
67
+
68
+ | **Dataset** | **Language** | **Category** | **Symmetry** | **Reference** | **Format** | **HN Mine** | **Size** | **Deduped Size** | **Duplicates** |
69
+ |---------------------------------------------------------|--------------|------------------------------|--------------|---------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------|----------|------------------|----------------|
70
+ | agnews | English | News | Asymmetric | [AG news corpus](http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html) | (Title, Description, Negatives) of news articles from the AG News dataset | bge-base-en-v1.5 mine | 1157745 | 1157745 | 0 |
71
+ | AllNLI | English | NLI | Symmetric | [SNLI and MNLI](https://huggingface.co/datasets/multi_nli) | (Anchor, Entailment_Text, Contradiction_Text) - Combination of SNLI + MultiNLI Triplets | Sentence Transformers Train HN | 277230 | 277230 | 0 |
72
+ | altlex | English | Wikipedia Pair | Symmetric | [altlex](https://github.com/chridey/altlex/) | (English_Wikipedia, Simple_English_Wikipedia, Negatives) - Matched pairs | bge-base-en-v1.5 mine | 112696 | 112696 | 0 |
73
+ | amazon_review_2018_1m | English | Amazon | Asymmetric | [Amazon review data (2018)](http://deepyeti.ucsd.edu/jianmo/amazon/index.html) | (Title, review, Negatives) from Amazon. Only Top 1 million samples are used here to shrink the dataset sizes. | bge-base-en-v1.5 mine | 1000000 | 999999 | 1 |
74
+ | cnn_dailymail | English | News | Asymmetric | [CNN Dailymail Dataset](https://huggingface.co/datasets/cnn_dailymail) | (highlight sentences, article) with all highlight sentences as one text for each news article | bge-base-en-v1.5 mine | 311971 | 311971 | 0 |
75
+ | codesearchnet | English | Github | Asymmetric | [CodeSearchNet](https://huggingface.co/datasets/code_search_net) | (Comment, Code, Negatives) - pairs from opensource libraries hosted on GitHub. It contains code and documentation for several programming languages. | bge-base-en-v1.5 mine | 1375067 | 1375067 | 0 |
76
+ | dureader | Chinese | Multilingual Web Collections | Asymmetric | [DuReader Retrieval](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval) | (Question, Answer, Negatives) | Use originally provided HN | 86395 | 86395 | 0 |
77
+ | eli5_question_answer | English | Reddit | Asymmetric | [ELI5](https://huggingface.co/datasets/eli5) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 325475 | 325390 | 85 |
78
+ | gooaq_pairs | English | Web Collections | Asymmetric | [GooAQ](https://github.com/allenai/gooaq) | (Question, Answer, Negatives) - Pairs from Google auto suggest | bge-base-en-v1.5 mine | 3012496 | 3012347 | 149 |
79
+ | hotpotqa | English | Wikipedia QA | Asymmetric | [HotpotQA](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/hotpotqa.zip) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 85000 | 85000 | 0 |
80
+ | medmcqa | English | Medical | Asymmetric | [MedMCQA](https://huggingface.co/datasets/openlifescienceai/medmcqa) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 160869 | 160865 | 4 |
81
+ | miracl | 16 languages | Multilingual Wikipedia | Asymmetric | [MIRACL](https://huggingface.co/datasets/miracl/miracl) | (Question, Answer, Negatives) | Use originally provided HN | 32561 | 32405 | 156 |
82
+ | mr_tydi_combined | 11 languages | Multilingual Wikipedia | Asymmetric | [Mr. TyDi](https://huggingface.co/datasets/castorini/mr-tydi) | (Question, Answer, Negatives) | Use originally provided HN | 48715 | 48475 | 240 |
83
+ | msmarco | English | Web Collections | Asymmetric | [MS MARCO Passages](https://github.com/microsoft/MSMARCO-Passage-Ranking) | (Question, Answer, Negatives) | bowdpr HN by following [this link](https://github.com/ma787639046/bowdpr) | 502939 | 502854 | 85 |
84
+ | nq | English | Wikipedia QA | Asymmetric | [NQ](https://github.com/facebookresearch/DPR) | (Question, Answer, Negatives) | bowdpr HN by following [this link](https://github.com/ma787639046/bowdpr) | 58812 | 58800 | 12 |
85
+ | quora_duplicates_triplets | English | Forum Duplicates | Symmetric | [QQP](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs) | (Question, Duplicated Question, Negatives) - Duplicate question pairs from Quora | Sentence Transformers Train HN | 101762 | 97011 | 4751 |
86
+ | searchQA_top5_snippets | English | Web Collections | Asymmetric | [search_qa](https://huggingface.co/datasets/search_qa) | (Question, Top5 text snippets, Negatives) from SearchQA dataset. | bge-base-en-v1.5 mine | 117220 | 117219 | 1 |
87
+ | sentence-compression | English | News | Asymmetric | [Sentence-Compression](https://github.com/google-research-datasets/sentence-compression) | (Long text, short text) about sentence-compression | bge-base-en-v1.5 mine | 180000 | 180000 | 0 |
88
+ | SimpleWiki | English | Wikipedia Pair | Symmetric | [SimpleWiki](https://cs.pomona.edu/~dkauchak/simplification/) | (English_Wikipedia, Simple_English_Wikipedia, Negatives) matched pairs | bge-base-en-v1.5 mine | 102225 | 102225 | 0 |
89
+ | squad_pairs | English | Wikipedia QA | Asymmetric | [SQuAD](https://huggingface.co/datasets/squad) | (Question, Answer, Negatives) | bge-base-en-v1.5 mine | 87599 | 87595 | 4 |
90
+ | stackexchange_duplicate_questions_title-body_title-body | English | Forum Duplicates | Symmetric | [Stack Exchange Data API](https://data.stackexchange.com/apple/query/fork/1456963) | (Title-Body, Duplicated Title-Body, Negatives) - pairs of duplicate questions from StackExchange | bge-base-en-v1.5 mine | 250519 | 250516 | 3 |
91
+ | t2ranking | Chinese | Multilingual Web Collections | Asymmetric | [T2Ranking](https://github.com/THUIR/T2Ranking/) | (Question, Answer, Negatives) | Use originally provided HN | 200376 | 200376 | 0 |
92
+ | trivia | English | Wikipedia QA | Asymmetric | [Trivia QA](https://github.com/facebookresearch/DPR) | (Question, Answer, Negatives) | bowdpr HN by following [this link](https://github.com/ma787639046/bowdpr) | 60380 | 60370 | 10 |
93
+ | xsum | English | News | Asymmetric | [xsum](https://huggingface.co/datasets/xsum) | (Summary, News Article) pairs from XSUM dataset | bge-base-en-v1.5 mine | 226711 | 226711 | 0 |
94
+ | yahoo_answers_title_answer | English | Yahoo | Asymmetric | [Yahoo Answers](https://www.kaggle.com/soumikrakshit/yahoo-answers-dataset) | (Title, Answer, Negatives) | bge-base-en-v1.5 mine | 1198260 | 1198018 | 242 |
95
+ | **Total Lines** | | | | | | | 11073023 | 11067280 | 5743 |
96
+
97
+ ## Cite
98
+ If you are interested in our work, please consider citing our paper.
99
+
100
+ ```bibtex
101
+ @article{ma2024tdro,
102
+ author = {Guangyuan Ma and
103
+ Yongliang Ma and
104
+ Xing Wu and
105
+ Zhenpeng Su and
106
+ Ming Zhou and
107
+ Songlin Hu},
108
+ title = {Task-level Distributionally Robust Optimization for Large Language
109
+ Model-based Dense Retrieval},
110
+ journal = {CoRR},
111
+ volume = {abs/2408.10613},
112
+ year = {2024},
113
+ url = {https://doi.org/10.48550/arXiv.2408.10613},
114
+ doi = {10.48550/ARXIV.2408.10613},
115
+ eprinttype = {arXiv},
116
+ eprint = {2408.10613},
117
+ timestamp = {Tue, 24 Sep 2024 17:36:32 +0200},
118
+ }
119
+ ```
120
+
121
+
122
+
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+