स्विस_निर्णय_भविष्यवाणी

सन्दर्भ:

डे

इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:

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

विवरण :

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.

लाइसेंस : कोई ज्ञात लाइसेंस नहीं
संस्करण : 1.0.0
विभाजन :

विभाजित करना	उदाहरण
`'test'`	9725
`'train'`	35458
`'validation'`	4705

विशेषताएँ :

{
    "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"
    }
}

फादर

इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:

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

विवरण :

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.

लाइसेंस : कोई ज्ञात लाइसेंस नहीं
संस्करण : 1.0.0
विभाजन :

विभाजित करना	उदाहरण
`'test'`	6820
`'train'`	21179
`'validation'`	3095

विशेषताएँ :

{
    "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"
    }
}

यह

इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:

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

विवरण :

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.

लाइसेंस : कोई ज्ञात लाइसेंस नहीं
संस्करण : 1.0.0
विभाजन :

विभाजित करना	उदाहरण
`'test'`	812
`'train'`	3072
`'validation'`	408

विशेषताएँ :

{
    "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"
    }
}

सभी_भाषाएँ

इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:

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

विवरण :

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.

लाइसेंस : कोई ज्ञात लाइसेंस नहीं
संस्करण : 1.0.0
विभाजन :

विभाजित करना	उदाहरण
`'test'`	17357
`'train'`	59709
`'validation'`	8208

विशेषताएँ :

{
    "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"
    }
}