swiss_judgment_prediction

Ссылки:

• Код
• Обнимающее лицо

де

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:swiss_judgment_prediction/de')

• Описание :

Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.  
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,  
to promote robustness and fairness studies on the critical area of legal NLP.

• Лицензия : Нет известной лицензии.
• Версия : 1.0.0
• Расколы :

Расколоть	Примеры
'test'	9725
'train'	35458
'validation'	4705

• Функции :

{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "year": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "dismissal",
            "approval"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "region": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "canton": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "legal area": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

фр.

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:swiss_judgment_prediction/fr')

• Описание :

Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.  
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,  
to promote robustness and fairness studies on the critical area of legal NLP.

• Лицензия : Нет известной лицензии.
• Версия : 1.0.0
• Расколы :

Расколоть	Примеры
'test'	6820
'train'	21179
'validation'	3095

• Функции :

{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "year": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "dismissal",
            "approval"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "region": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "canton": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "legal area": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

это

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:swiss_judgment_prediction/it')

• Описание :

Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.  
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,  
to promote robustness and fairness studies on the critical area of legal NLP.

• Лицензия : Нет известной лицензии.
• Версия : 1.0.0
• Расколы :

Расколоть	Примеры
'test'	812
'train'	3072
'validation'	408

• Функции :

{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "year": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "dismissal",
            "approval"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "region": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "canton": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "legal area": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

все_языки

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:swiss_judgment_prediction/all_languages')

• Описание :

Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.  
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,  
to promote robustness and fairness studies on the critical area of legal NLP.

• Лицензия : Нет известной лицензии.
• Версия : 1.0.0
• Расколы :

Расколоть	Примеры
'test'	17357
'train'	59709
'validation'	8208

• Функции :

{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "year": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "dismissal",
            "approval"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "region": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "canton": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "legal area": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}