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Update math_qa.py on GitHub
How to load this dataset directly with the
🤗/datasets library:
from datasets import load_dataset dataset = load_dataset("math_qa")
None yet. Start fine-tuning now =)
Update README.md on GitHub
Our dataset is gathered by using a new representation language to annotate over the AQuA-RAT dataset. AQuA-RAT has provided the questions, options, rationale, and the correct options.
We show detailed information for up to 5 configurations of the dataset.
An example of 'train' looks as follows.
{
"Problem": "a multiple choice test consists of 4 questions , and each question has 5 answer choices . in how many r ways can the test be completed if every question is unanswered ?",
"Rationale": "\"5 choices for each of the 4 questions , thus total r of 5 * 5 * 5 * 5 = 5 ^ 4 = 625 ways to answer all of them . answer : c .\"",
"annotated_formula": "power(5, 4)",
"category": "general",
"correct": "c",
"linear_formula": "power(n1,n0)|",
"options": "a ) 24 , b ) 120 , c ) 625 , d ) 720 , e ) 1024"
}The data fields are the same among all splits.
Problem: a string feature.Rationale: a string feature.options: a string feature.correct: a string feature.annotated_formula: a string feature.linear_formula: a string feature.category: a string feature.| name | train | validation | test |
|---|---|---|---|
| default | 29837 | 4475 | 2985 |