sentence1
sequence | sentence2
sequence | gold
sequence |
|---|---|---|
["Einen weiteren Oscar erhielt er 2013 für seine Regiearbeit an \"\".","Seine Eltern, Emigranten au(...TRUNCATED) | ["Other data that are used included Bragg diffraction data for crystalline materials, and EXAFS data(...TRUNCATED) | [[18,160943],[87,90155],[151,270238],[197,168375],[691,384926],[795,45818],[889,378624],[1126,336812(...TRUNCATED) |
Dataset Card for MTEB Benchmark
Dataset Summary
MTEB is a heterogeneous benchmark that has been built from diverse tasks:
- BitextMining: BUCC, Tatoeba
- Classification: AmazonCounterfactualClassification, AmazonPolarityClassification, AmazonReviewsClassification, Banking77Classification, EmotionClassification, ImdbClassification, MassiveIntentClassification, MassiveScenarioClassification, MTOPDomainClassification, MTOPIntentClassification, ToxicConversationsClassification, TweetSentimentExtractionClassification
- Clustering: ArxivClusteringP2P, ArxivClusteringS2S, BiorxivClusteringP2P, BiorxivClusteringS2S, MedrxivClusteringP2P, MedrxivClusteringS2S, RedditClustering, RedditClusteringP2P, StackExchangeClustering, StackExchangeClusteringP2P, TwentyNewsgroupsClustering
- Pair Classification: SprintDuplicateQuestions, TwitterSemEval2015, TwitterURLCorpus
- Reranking: AskUbuntuDupQuestions, MindSmallReranking, SciDocs, StackOverflowDupQuestions
- Retrieval: ArguAna, ClimateFEVER, CQADupstackRetrieval, DBPedia, FEVER, FiQA2018, HotpotQA, MSMARCO, MSMARCOv2, NFCorpus, NQ, QuoraRetrieval, SCIDOCS, SciFact, Touche2020, TRECCOVID
- STS: BIOSSES, SICK-R, STS12, STS13, STS14, STS15, STS16, STS17, STS22, STSBenchmark
- Summarization: SummEval
All these datasets have been preprocessed and can be used for your experiments.
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