tweet_eval

Références :

émoticône

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

ds = tfds.load('huggingface:tweet_eval/emoji')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 50000
'train' 45000
'validation' 5000
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 20,
        "names": [
            "\u2764",
            "\ud83d\ude0d",
            "\ud83d\ude02",
            "\ud83d\udc95",
            "\ud83d\udd25",
            "\ud83d\ude0a",
            "\ud83d\ude0e",
            "\u2728",
            "\ud83d\udc99",
            "\ud83d\ude18",
            "\ud83d\udcf7",
            "\ud83c\uddfa\ud83c\uddf8",
            "\u2600",
            "\ud83d\udc9c",
            "\ud83d\ude09",
            "\ud83d\udcaf",
            "\ud83d\ude01",
            "\ud83c\udf84",
            "\ud83d\udcf8",
            "\ud83d\ude1c"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

émotion

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

ds = tfds.load('huggingface:tweet_eval/emotion')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 1421
'train' 3257
'validation' 374
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 4,
        "names": [
            "anger",
            "joy",
            "optimism",
            "sadness"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

détester

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

ds = tfds.load('huggingface:tweet_eval/hate')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 2970
'train' 9000
'validation' 1000
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "non-hate",
            "hate"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ironie

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

ds = tfds.load('huggingface:tweet_eval/irony')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 784
'train' 2862
'validation' 955
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "non_irony",
            "irony"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

offensant

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

ds = tfds.load('huggingface:tweet_eval/offensive')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 860
'train' 11916
'validation' 1324
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "non-offensive",
            "offensive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

sentiment

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

ds = tfds.load('huggingface:tweet_eval/sentiment')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 12284
'train' 45615
'validation' 2000
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "negative",
            "neutral",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

position_avortement

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

ds = tfds.load('huggingface:tweet_eval/stance_abortion')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 280
'train' 587
'validation' 66
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "none",
            "against",
            "favor"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

position_athéisme

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

ds = tfds.load('huggingface:tweet_eval/stance_atheism')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 220
'train' 461
'validation' 52
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "none",
            "against",
            "favor"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

position_climate

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

ds = tfds.load('huggingface:tweet_eval/stance_climate')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 169
'train' 355
'validation' 40
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "none",
            "against",
            "favor"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

position_féministe

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

ds = tfds.load('huggingface:tweet_eval/stance_feminist')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 285
'train' 597
'validation' 67
  • Caractéristiques : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "none",
            "against",
            "favor"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

position_hillary

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

ds = tfds.load('huggingface:tweet_eval/stance_hillary')
  • Description :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 295
'train' 620
'validation' 69
  • Caractéristiques :
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "none",
            "against",
            "favor"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}