task_categories:text-generation size_categories:100K<n<1M language:en license:apache-2.0 arithmetics region:us
---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- arithmetics
pretty_name: RedPajama Arithmetics
size_categories:
- 100K<n<1M
---

## Dataset Summary

The Arithmetic Operations Dataset is a synteticly generated collection of mathematical arithmetic operations for practice and evaluation purposes. It contains a total of 624,800 arithmetic operations, consisting of 568,000 addition operations and 56,800 subtraction operations. The dataset is designed to provide a range of arithmetic problems to train and evaluate language models for solving simple arithmetic (mostly addition, the others TBA) problems.

## Dataset Structure

The dataset is organized into two main categories: addition and subtraction. Each category contains a set of arithmetic operations in separate files (`addition.json`) and (`subtraction.json`), and the file (`dataset.json`) provides combined data from both.

### Data Instances

```bash
{
    "instruction": "What is the answer to 373486002216116154 + 339369?",
    "input": "373486002216116154 + 339369",
    "output": "373486002216116154 + 339369 = 373486002216455523",
    "answer": "373486002216455523"
},
{
    "instruction": "9916607491627649 minus 581954",
    "input": "9916607491627649 - 581954",
    "output": "9916607491627649 - 581954 = 9916607491045695",
    "answer": "9916607491045695"
},

```

### Data Fields
The files share the same structure and have 4 fields:
- `instruction`: Human instructions are generated by inserting arithmetic expressions into randomly selected templates and incorporating natural language variations. These instructions are intended to serve as prompts for instruction-finetuning, providing input for training the model.
- `input`: A randomly generated arithmetic expression, that can serve as a substitute for the 'instruction' component during training, allowing a specific focus on arithmetic operations while minimizing the impact of natural language.
- `output`: the target output for the model to learn.
- `answer`: direct numerical answer to the arithmetic task. It can be used to test learnability of various sub-tasks.

## Contact

For any questions or inquiries regarding this dataset, please contact xufana@yandex.ru.
