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Models/AlBERT

AlBERT

Reported on 16 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 Processing8 results

  • Text ClassificationonCivil Comments
    AUROC· 2023-01-26
    0.979
    best: 0.9818 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    GMB BNSP· 2023-01-26
    0.9499
    best: 0.9644 (DistilBERT)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    GMB BPSN· 2023-01-26
    0.8982
    best: 0.901 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    GMB Subgroup· 2023-01-26
    0.8734
    best: 0.8807 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    Macro F1· 2023-01-26
    0.3541
    best: 0.4749 (RoBERTa BCE)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • Text ClassificationonCivil Comments
    Micro F1· 2023-01-26
    0.4845
    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
    0.3247
    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
    0.9104
    best: 0.9254 (XLNet)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125

Methodology8 results

  • ClassificationonCivil Comments
    AUROC· 2023-01-26
    0.979
    best: 0.9818 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    GMB BNSP· 2023-01-26
    0.9499
    best: 0.9644 (DistilBERT)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    GMB BPSN· 2023-01-26
    0.8982
    best: 0.901 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    GMB Subgroup· 2023-01-26
    0.8734
    best: 0.8807 (RoBERTa Focal Loss)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    Macro F1· 2023-01-26
    0.3541
    best: 0.4749 (RoBERTa BCE)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125
  • ClassificationonCivil Comments
    Micro F1· 2023-01-26
    0.4845
    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
    0.3247
    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
    0.9104
    best: 0.9254 (XLNet)
    A benchmark for toxic comment classification on Civil Comments datasetarXiv:2301.11125