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Models/Glyce + BERT

Glyce + BERT

Reported on 24 benchmarks across 2 tasks · 1 paper · 24 SOTA

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

Natural Language Processing24 results

  • ChineseonCITYU
    F1· 2019-01-29
    97.9
    best: 97.93 (WMSeg + ZEN)
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonCITYU
    Precision· 2019-01-29
    97.9
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonCITYU
    Recall· 2019-01-29
    98
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonAS
    F1· 2019-01-29
    96.7
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonAS
    Precision· 2019-01-29
    96.6
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonAS
    Recall· 2019-01-29
    96.8
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonPKU
    F1· 2019-01-29
    96.7
    best: 96.84 (BABERT-LE)
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonPKU
    Precision· 2019-01-29
    97.1
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonPKU
    Recall· 2019-01-29
    96.4
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonMSR
    F1· 2019-01-29
    98.3
    best: 98.63 (BABERT-LE)
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonMSR
    Precision· 2019-01-29
    98.2
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • ChineseonMSR
    Recall· 2019-01-29
    98.3
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onWeibo NER
    F1· 2019-01-29
    67.6
    best: 72.77 (BERT-CRF (Replicated in AdaSeq))
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onWeibo NER
    Precision· 2019-01-29
    67.68
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onWeibo NER
    Recall· 2019-01-29
    67.71
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onMSRA
    F1· 2019-01-29
    95.54
    best: 96.72 (BERT-MRC+DSC)
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onMSRA
    Precision· 2019-01-29
    95.57
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onMSRA
    Recall· 2019-01-29
    95.51
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onResume NER
    F1· 2019-01-29
    96.54
    best: 96.87 (BERT-CRF (Replicated in AdaSeq))
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onResume NER
    Precision· 2019-01-29
    96.62
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onResume NER
    Recall· 2019-01-29
    96.48
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onOntoNotes 4
    F1· 2019-01-29
    80.62
    best: 84.47 (BERT-MRC+DSC)
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onOntoNotes 4
    Precision· 2019-01-29
    81.87
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125
  • Named Entity Recognition (NER)onOntoNotes 4
    Recall· 2019-01-29
    81.4
    SOTA
    Glyce: Glyph-vectors for Chinese Character RepresentationsarXiv:1901.10125