pares_corvos

Referências:

pares_corvos

Use o seguinte comando para carregar esse conjunto de dados no TFDS:

ds = tfds.load('huggingface:crows_pairs/crows_pairs')
  • Descrição :
CrowS-Pairs, a challenge dataset for measuring the degree to which U.S. stereotypical biases present in the masked language models (MLMs).
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 1508
  • Características :
{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "sent_more": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sent_less": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stereo_antistereo": {
        "num_classes": 2,
        "names": [
            "stereo",
            "antistereo"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "bias_type": {
        "num_classes": 9,
        "names": [
            "race-color",
            "socioeconomic",
            "gender",
            "disability",
            "nationality",
            "sexual-orientation",
            "physical-appearance",
            "religion",
            "age"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "annotations": {
        "feature": {
            "feature": {
                "num_classes": 9,
                "names": [
                    "race-color",
                    "socioeconomic",
                    "gender",
                    "disability",
                    "nationality",
                    "sexual-orientation",
                    "physical-appearance",
                    "religion",
                    "age"
                ],
                "names_file": null,
                "id": null,
                "_type": "ClassLabel"
            },
            "length": -1,
            "id": null,
            "_type": "Sequence"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "anon_writer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "anon_annotators": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}