powiedział-br

Bibliografia:

wieloetykietowe

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

ds = tfds.load('huggingface:told-br/multilabel')
  • Opis :
ToLD-Br is the biggest dataset for toxic tweets in Brazilian Portuguese, crowdsourced
by 42 annotators selected from a pool of 129 volunteers. Annotators were selected aiming
to create a plural group in terms of demographics (ethnicity, sexual orientation, age, gender).
Each tweet was labeled by three annotators in 6 possible categories:
LGBTQ+phobia,Xenophobia, Obscene, Insult, Misogyny and Racism.
Podział Przykłady
'train' 21000
  • Cechy :
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "homophobia": {
        "num_classes": 4,
        "names": [
            "zero_votes",
            "one_vote",
            "two_votes",
            "three_votes"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "obscene": {
        "num_classes": 4,
        "names": [
            "zero_votes",
            "one_vote",
            "two_votes",
            "three_votes"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "insult": {
        "num_classes": 4,
        "names": [
            "zero_votes",
            "one_vote",
            "two_votes",
            "three_votes"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "racism": {
        "num_classes": 4,
        "names": [
            "zero_votes",
            "one_vote",
            "two_votes",
            "three_votes"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "misogyny": {
        "num_classes": 4,
        "names": [
            "zero_votes",
            "one_vote",
            "two_votes",
            "three_votes"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "xenophobia": {
        "num_classes": 4,
        "names": [
            "zero_votes",
            "one_vote",
            "two_votes",
            "three_votes"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

dwójkowy

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

ds = tfds.load('huggingface:told-br/binary')
  • Opis :
ToLD-Br is the biggest dataset for toxic tweets in Brazilian Portuguese, crowdsourced
by 42 annotators selected from a pool of 129 volunteers. Annotators were selected aiming
to create a plural group in terms of demographics (ethnicity, sexual orientation, age, gender).
Each tweet was labeled by three annotators in 6 possible categories:
LGBTQ+phobia,Xenophobia, Obscene, Insult, Misogyny and Racism.
Podział Przykłady
'test' 2100
'train' 16800
'validation' 2100
  • Cechy :
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "not-toxic",
            "toxic"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}