swiss_judgment_prediction

Referencje:

de

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

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

Opis :

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.

Licencja : Brak znanej licencji
Wersja : 1.0.0
Podziały :

Podział	Przykłady
`'test'`	9725
`'train'`	35458
`'validation'`	4705

Cechy :

{
    "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"
    }
}

ks

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

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

Opis :

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.

Licencja : Brak znanej licencji
Wersja : 1.0.0
Podziały :

Podział	Przykłady
`'test'`	6820
`'train'`	21179
`'validation'`	3095

Cechy :

{
    "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"
    }
}

To

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

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

Opis :

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.

Licencja : Brak znanej licencji
Wersja : 1.0.0
Podziały :

Podział	Przykłady
`'test'`	812
`'train'`	3072
`'validation'`	408

Cechy :

{
    "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"
    }
}

wszystkie_języki

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

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

Opis :

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.

Licencja : Brak znanej licencji
Wersja : 1.0.0
Podziały :

Podział	Przykłady
`'test'`	17357
`'train'`	59709
`'validation'`	8208

Cechy :

{
    "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"
    }
}