참고자료:
연령_분류
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:matinf/age_classification')
- 설명 :
MATINF is the first jointly labeled large-scale dataset for classification, question answering and summarization.
MATINF contains 1.07 million question-answer pairs with human-labeled categories and user-generated question
descriptions. Based on such rich information, MATINF is applicable for three major NLP tasks, including classification,
question answering, and summarization. We benchmark existing methods and a novel multi-task baseline over MATINF to
inspire further research. Our comprehensive comparison and experiments over MATINF and other datasets demonstrate the
merits held by MATINF.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
나뉘다 | 예 |
---|---|
'test' | 38318 |
'train' | 134852 |
'validation' | 19323 |
- 특징 :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"description": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"0-1\u5c81",
"1-2\u5c81",
"2-3\u5c81"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
주제_분류
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:matinf/topic_classification')
- 설명 :
MATINF is the first jointly labeled large-scale dataset for classification, question answering and summarization.
MATINF contains 1.07 million question-answer pairs with human-labeled categories and user-generated question
descriptions. Based on such rich information, MATINF is applicable for three major NLP tasks, including classification,
question answering, and summarization. We benchmark existing methods and a novel multi-task baseline over MATINF to
inspire further research. Our comprehensive comparison and experiments over MATINF and other datasets demonstrate the
merits held by MATINF.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
나뉘다 | 예 |
---|---|
'test' | 175363 |
'train' | 613036 |
'validation' | 87519 |
- 특징 :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"description": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 18,
"names": [
"\u4ea7\u8925\u671f\u4fdd\u5065",
"\u513f\u7ae5\u8fc7\u654f",
"\u52a8\u4f5c\u53d1\u80b2",
"\u5a74\u5e7c\u4fdd\u5065",
"\u5a74\u5e7c\u5fc3\u7406",
"\u5a74\u5e7c\u65e9\u6559",
"\u5a74\u5e7c\u671f\u5582\u517b",
"\u5a74\u5e7c\u8425\u517b",
"\u5b55\u671f\u4fdd\u5065",
"\u5bb6\u5ead\u6559\u80b2",
"\u5e7c\u513f\u56ed",
"\u672a\u51c6\u7236\u6bcd",
"\u6d41\u4ea7\u548c\u4e0d\u5b55",
"\u75ab\u82d7\u63a5\u79cd",
"\u76ae\u80a4\u62a4\u7406",
"\u5b9d\u5b9d\u4e0a\u706b",
"\u8179\u6cfb",
"\u5a74\u5e7c\u5e38\u89c1\u75c5"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
요약
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:matinf/summarization')
- 설명 :
MATINF is the first jointly labeled large-scale dataset for classification, question answering and summarization.
MATINF contains 1.07 million question-answer pairs with human-labeled categories and user-generated question
descriptions. Based on such rich information, MATINF is applicable for three major NLP tasks, including classification,
question answering, and summarization. We benchmark existing methods and a novel multi-task baseline over MATINF to
inspire further research. Our comprehensive comparison and experiments over MATINF and other datasets demonstrate the
merits held by MATINF.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
나뉘다 | 예 |
---|---|
'test' | 213681 |
'train' | 747888 |
'validation' | 106842 |
- 특징 :
{
"description": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
qa
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:matinf/qa')
- 설명 :
MATINF is the first jointly labeled large-scale dataset for classification, question answering and summarization.
MATINF contains 1.07 million question-answer pairs with human-labeled categories and user-generated question
descriptions. Based on such rich information, MATINF is applicable for three major NLP tasks, including classification,
question answering, and summarization. We benchmark existing methods and a novel multi-task baseline over MATINF to
inspire further research. Our comprehensive comparison and experiments over MATINF and other datasets demonstrate the
merits held by MATINF.
- 라이센스 : 알려진 라이센스 없음
- 버전 : 1.0.0
- 분할 :
나뉘다 | 예 |
---|---|
'test' | 213681 |
'train' | 747888 |
'validation' | 106842 |
- 특징 :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}