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Models/MPNet

MPNet

Reported on 8 benchmarks across 8 tasks · 2 papers

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

Natural Language Processing3 results

  • Semantic Textual SimilarityonMTEB
    Spearman Correlation· 2022-10-13
    80.28
    best: 84.54 (AnglE-UAE)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • Text ClusteringonMTEB
    V-Measure· 2022-10-13
    43.69
    best: 43.71 (ST5-XXL)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • Text ClassificationonMTEB
    Accuracy· 2022-10-13
    65.07
    best: 73.42 (ST5-XXL)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316

Methodology2 results

  • RetrievalonMTEB
    nDCG@10· 2022-10-13
    43.81
    best: 50.25 (SGPT-5.8B-msmarco)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316
  • ClassificationonMTEB
    Accuracy· 2022-10-13
    65.07
    best: 73.42 (ST5-XXL)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316

Computer Vision2 results

  • Instance SegmentationonScanNet(v2)
    mAP @ 50· 2020-01-06
    31
    best: 81.6 (Relation3D)
    Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance SegmentationarXiv:2001.01349
  • 3D Instance SegmentationonScanNet(v2)
    mAP @ 50· 2020-01-06
    31
    best: 81.6 (Relation3D)
    Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance SegmentationarXiv:2001.01349

Knowledge Base1 result

  • Text SummarizationonMTEB
    Spearman Correlation· 2022-10-13
    27.49
    best: 31.57 (MPNet-multilingual)
    MTEB: Massive Text Embedding BenchmarkarXiv:2210.07316