MCEval8K / dataset_infos copy.json
xzhao-tkl
Update readme
14a3ef0
raw
history blame
3.51 kB
{
"agnews": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"label": {
"_type": "ClassLabel",
"names": [
"World",
"Sports",
"Business",
"Sci/Tech"
]
}
},
"description": "Multi-choice, Topic classification task (Agnews)."
},
"amazon-reviews": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"label": {
"_type": "Value",
"dtype": "int8"
}
},
"description": "Multi-choice, Sentiment classification task with numerical labels (Amazon-Review)."
},
"imdb": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"label": {
"_type": "ClassLabel",
"names": [
"Negative",
"Positive"
]
}
},
"description": "Binary sentiment classification (IMDB)."
},
"commensenseqa": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"options": {
"feature": {
"_type": "Value",
"dtype": "string"
},
"length": 5,
"_type": "Sequence"
},
"label": {
"_type": "Value",
"dtype": "int8"
}
},
"description": "Multi-choice, Commense knowledge-answering datasets (CommensenseQA)."
},
"fever": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"label": {
"_type": "ClassLabel",
"names": [
"Incorrect",
"Correct"
]
}
},
"description": "Binary classification, fact-checking (FEVER)."
},
"myriadlama": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"options": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": 4,
"_type": "Sequence"
},
"label": {
"_type": "Value",
"dtype": "int8"
}
},
"description": "Multi-choice, open-domain knowledge question-answering (MyriadLAMA)."
},
"templama": {
"features": {
"text": {
"_type": "Value",
"dtype": "string"
},
"options": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": 4,
"_type": "Sequence"
},
"label": {
"_type": "Value",
"dtype": "int8"
}
},
"description": "Multi-choice, open-domain temporary knowledge QA (TempLAMA)."
}
}