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Models/GTR-XL

GTR-XL

Reported on 8 benchmarks across 7 tasks · 2 papers · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing5 results

  • Information RetrievalonPeerQA
    MRR· 2021-12-15
    0.4142
    best: 0.4845 (Dragon+)
    SOTA
    Large Dual Encoders Are Generalizable RetrieversarXiv:2112.07899
  • Semantic Textual SimilarityonMTEB
    Spearman Correlation· 2022-10-13
    77.8
    best: 84.54 (AnglE-UAE)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • Text ClusteringonMTEB
    V-Measure· 2022-10-13
    41.51
    best: 43.71 (ST5-XXL)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • Text ClassificationonMTEB
    Accuracy· 2022-10-13
    67.11
    best: 73.42 (ST5-XXL)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • Information RetrievalonPeerQA
    Recall@10· 2021-12-15
    0.6122
    best: 0.6851 (SPLADEv3)
    Large Dual Encoders Are Generalizable RetrieversarXiv:2112.07899

Methodology2 results

  • RetrievalonMTEB
    nDCG@10· 2022-10-13
    47.96
    best: 50.25 (SGPT-5.8B-msmarco)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • ClassificationonMTEB
    Accuracy· 2022-10-13
    67.11
    best: 73.42 (ST5-XXL)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316

Knowledge Base1 result

  • Text SummarizationonMTEB
    Spearman Correlation· 2022-10-13
    30.21
    best: 31.57 (MPNet-multilingual)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316