참고자료:
드
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:swiss_judgment_prediction/de')
- 설명 :
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.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 9725 |
'train' | 35458 |
'validation' | 4705 |
- 특징 :
{
"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"
}
}
정말로
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:swiss_judgment_prediction/fr')
- 설명 :
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.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 6820 |
'train' | 21179 |
'validation' | 3095 |
- 특징 :
{
"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"
}
}
그것
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:swiss_judgment_prediction/it')
- 설명 :
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.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 812 |
'train' | 3072 |
'validation' | 408 |
- 특징 :
{
"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"
}
}
모든_언어
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:swiss_judgment_prediction/all_languages')
- 설명 :
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.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 17357 |
'train' | 59709 |
'validation' | 8208 |
- 특징 :
{
"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"
}
}