| --- |
| task_categories: |
| - text-generation |
| - text2text-generation |
| language: |
| - en |
| tags: |
| - coding |
| - code generation |
| - atcoder |
| - programming contests |
| pretty_name: Atcoder's ABC Contests (Small) |
| size_categories: |
| - 100K<n<1M |
| --- |
| ## Dataset Description |
|
|
| - **Homepage:** None |
| - **Repository:** <https://huggingface.co/datasets/Nan-Do/atcoder_contests_small> |
| - **Paper:** None |
| - **Leaderboard:** None |
| - **Point of Contact:** [@Nan-Do](https://github.com/Nan-Do) |
|
|
| ### Dataset Summary |
|
|
| - This dataset aims to **facilitate the creation of sophisticated, multi-turn dialogue datasets focused on coding** |
| that could be used for **training reasoning Large Language Models (LLMs)**, particularly for **Supervised Fine-Tuning (SFT) and Knowledge Distillation** techniques. |
| - It also serves as a **robust foundation for problem-solving** in Large Language Models (LLMs). |
| - The dataset includes both **accepted and failed solutions** from Atcoders's (ABC) contests. |
| - In total, it features **1911 unique problems** and **384,536 submissions** across over **50 different programming languages (including the different versions)**. |
| - It covers contests from ABC contest 50 (previous contests only have the statements in japanese) up to ABC contest 350 **(April 20, 2024)**. |
|
|
| (If you are interested in accessing the dataset **please contact me [here](mailto:tarin.f@gmail.com)**) |
|
|
| ### Multi-turn dialogue |
|
|
| A multi-turn dialogue can be structured as follows: |
|
|
| - [USER] - Given the problem statement below, please provide a solution in {lang}. |
| - [SYSTEM] - Sure! Here's a solution in {lang}. [...] (Using a TLE submission) |
| - [USER] - The provided solution is too slow. Can you suggest a faster implementation? |
| - [SYSTEM] - Of course! Here's an optimized solution. [...] (Using an ACC submission) |
|
|
| This template is versatile and can be adjusted **to accommodate various scenarios** and/or **expanded** to |
| facilitate **high-quality conversations** for training Large Language Models (LLMs). |
|
|
| ### Languages |
|
|
| The problem descriptions are in English. |
| The dataset includes submissions in various programming languages, each with specific language and compiler versions. |
| For example, for **C++**: |
| Version | Compiler |
| :--------|:--------- |
| C++ 20 | Gcc 12.2 |
| C++ 17 | Gcc 12.2 |
| C++ 23 | Gcc 12.2 |
| C++ 23 | Clang 16.0.6 |
| C++ 20 | Clang 16.0.6 |
| C++ 17 | Clang 16.0.6 |
| C++ | GCC 9.2.1 |
|
|
| Here is a summary of the languages used for the submissions: |
| Programming Language | Total |
| :-----|:----- |
| cpp | 236325 |
| python3 | 106360 |
| rust | 11134 |
| java | 6652 |
| csharp | 4141 |
| c | 3867 |
| golang | 2970 |
| javascript | 1478 |
| php | 863 |
| kotlin | 337 |
| typescript | 330 |
| swift | 310 |
| common lisp | 176 |
| scala | 117 |
| dart | 36 |
| vim | 19 |
|
|
| ## Status |
|
|
| The status indicates the outcome of each submission. |
| Below is an explanation of the status values, their meanings, and their totals: |
| Value | Meaning | Total |
| :-----|:--------|:----- |
| AC | Submission Accepted | 338811 |
| WA | Wrong Answer | 34964 |
| RE | Runtime Error | 5858 |
| TLE | Time Limit Exceeded | 4861 |
| MLE | Memory Limit Exceeded| 42 |
|
|
| ### Data Splits |
|
|
| There are no splits (Only training). |
|
|
| ## Dataset Creation |
|
|
| Jun of 2024 |
|
|
| ### Curation Rationale |
|
|
| This dataset was designed to enhance the **coding** and **problem-solving** capabilities of LLMs by providing |
| **sophisticated multi-turn dialogues** focused on coding. |
|
|
| ### Source Data |
|
|
| The source of the dataset is [Atcoder's contests](https://atcoder.jp/) |
|
|
| ### Annotations |
|
|
| The dataset includes the following columns: |
|
|
| - **contest_id**: ID of the contest (e.g., abc-250). |
| - **problem_statement**: Markdown explanation of the problem. |
| - **task**: Task identifier within the contest (e.g., A). |
| - **lang**: Programming language used for the solution (see previous table for details). |
| - **score**: Score awarded for the task (e.g., 100, or 0 if failed). |
| - **code_size**: Size of the code in bytes. |
| - **status**: Outcome of the submission (see previous table for details). |
| - **execution_time**: Time taken by the submission in milliseconds. |
| - **execution_memory**: Memory used by the submission in kilobytes. |
| - **code**: Code that solves the problem. |
| |
| ## Citation |
| |
| If you get access to the dataset find the dataset useful in your work, please consider citing it as: |
| |
| ```bibtex |
| @misc{tarin2024atcoder, |
| title={Atcoder ABC Contests (Small)}, |
| author={Fernando Tarin Morales}, |
| year={2024}, |
| publisher = {Hugging Face}, |
| journal = {Hugging Face repository}, |
| howpublished = {\url{https://huggingface.co/datasets/Nan-Do/atcoder_abc_contests_small}} |
| } |
| ``` |
| |
| If you have any suggestion, comment or proposal, please contact me [here](mailto:tarin.f@gmail.com) |
