swiss_judgment_prediction

อ้างอิง:

เดอ

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

คำอธิบาย :

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.

ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
เวอร์ชัน : 1.0.0
แยก :

แยก	ตัวอย่าง
`'test'`	9725
`'train'`	35458
`'validation'`	4705

คุณสมบัติ :

{
    "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"
    }
}

ศ

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

คำอธิบาย :

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.

ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
เวอร์ชัน : 1.0.0
แยก :

แยก	ตัวอย่าง
`'test'`	6820
`'train'`	21179
`'validation'`	3095

คุณสมบัติ :

{
    "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"
    }
}

มัน

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

คำอธิบาย :

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.

ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
เวอร์ชัน : 1.0.0
แยก :

แยก	ตัวอย่าง
`'test'`	812
`'train'`	3072
`'validation'`	408

คุณสมบัติ :

{
    "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"
    }
}

ทุก_ภาษา

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

คำอธิบาย :

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.

ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
เวอร์ชัน : 1.0.0
แยก :

แยก	ตัวอย่าง
`'test'`	17357
`'train'`	59709
`'validation'`	8208

คุณสมบัติ :

{
    "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"
    }
}