Aravindhan11/fine_tune

---
pretty_name: Math Question Answer Verification Competition
dataset_info:
features:
- name: question
dtype: string
- name: is_correct
dtype: bool
- name: answer
dtype: string
- name: solution
dtype: string
splits:
- name: train
num_bytes: 755580540
num_examples: 1000000
- name: test
num_bytes: 7516001
num_examples: 10000
download_size: 394320280
dataset_size: 763096541
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# Math Question Answer Verification Competition Dataset

## Dataset Description

The dataset for this task is the [Math Question Answer Verification Competition dataset](https://huggingface.co/datasets/ad6398/nyu-dl-teach-maths-comp), available on Hugging Face.
It consists of questions from various math topics, structured into several columns:
- **question**: The math question posed to the student.
- **answer**: The ideal or correct answer to the question.
- **solution**: A detailed reasoning or solution that explains the answer, which participants can use to enhance their model’s understanding of the answer's correctness.
- **is_correct**: The target variable for this competition, indicating whether the answer provided is correct (True) or incorrect (False).

**Note:** the label (i.e is_correct) in test set is just a placeholder, all set to True.

## Objective

Participants will build a model to predict the value in the "is_correct" column for the test set. The model could leverage both the answer and the accompanying explanation to capture nuanced indicators of correct reasoning and identify patterns that differentiate correct answers from incorrect ones.

## Dataset Loading Instructions

To access the dataset in your code, you can load it directly from Hugging Face’s `datasets` library with the following code snippet:

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("ad6398/nyu-dl-teach-maths-comp")
train_dataset = dataset['train']
test_dataset = dataset['test']