tmu_gfm_dataset

Referencje:

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:tmu_gfm_dataset')
  • Opis :
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).
  • Licencja : Brak znanej licencji
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'train' 4221
  • Cechy :
{
    "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"
    }
}