tmu_gfm_dataset

Références:

• Code
• Visage étreignant

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:tmu_gfm_dataset')

• Descriptif :

A dataset for GEC metrics with manual evaluations of grammaticality, fluency, and meaning preservation for system outputs. More detail about the creation of the dataset can be found in Yoshimura et al. (2020).

• Licence : Aucune licence connue
• Version : 1.1.0
• Fractionnements :

• Caractéristiques :

{
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "output": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "grammer": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "fluency": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "meaning": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "system": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ave_g": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    },
    "ave_f": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    },
    "ave_m": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    }
}