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Models/XLM RoBERTa

XLM RoBERTa

Reported on 8 benchmarks across 2 tasks · 1 paper

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

Natural Language Processing4 results

  • Text ClassificationonCivil Comments
    GMB BPSN· 2023-01-26
    0.8859
    best: 0.901 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    Micro F1· 2023-01-26
    0.468
    best: 0.5958 (Unfreeze Glove ResNet 44)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    Precision· 2023-01-26
    0.3135
    best: 0.4835 (Unfreeze Glove ResNet 44)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    Recall· 2023-01-26
    0.923
    best: 0.9254 (XLNet)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125

Methodology4 results

  • ClassificationonCivil Comments
    GMB BPSN· 2023-01-26
    0.8859
    best: 0.901 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    Micro F1· 2023-01-26
    0.468
    best: 0.5958 (Unfreeze Glove ResNet 44)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    Precision· 2023-01-26
    0.3135
    best: 0.4835 (Unfreeze Glove ResNet 44)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    Recall· 2023-01-26
    0.923
    best: 0.9254 (XLNet)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125