Datasets:
File size: 4,358 Bytes
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language:
- en
- ar
- fr
- es
- de
- it
- pt
- zh
- ru
license: apache-2.0
annotations_creators:
- machine-generated
language_creators:
- machine-generated
multilinguality:
- multilingual
source_datasets:
- openai/gsm8k
task_categories:
- text-generation
tags:
- dpo
- math
- multilingual
- alignment
- gsm8k
- synthetic
- translation
- gpt-oss
- gpt-oss-20b
- llama-cpp
dataset_info:
features:
- name: prompt
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
- name: language
dtype: string
- name: prompt_en
dtype: string
- name: chosen_en
dtype: string
splits:
- name: train
num_bytes: 1488448
num_examples: 900
download_size: 747740
dataset_size: 1488448
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Mini-GSM8K-Multilingual-Alignment
A compact, multilingual DPO (Direct Preference Optimization) alignment dataset designed for training small language models to produce high-quality, step-by-step mathematical reasoning across multiple languages.
## Purpose
This dataset was created to improve multilingual math reasoning in small language models such as [Al-Khwarizmi-3B](https://huggingface.co/mzoelfakar/Al-Khwarizmi-3B) — a 3B-parameter math tutor model named after the 9th-century mathematician. The goal is to teach the model to prefer detailed, friendly, well-structured solutions over vague, uninformative responses, across 9 languages.
## How It Was Created
1. **Source**: 900 samples were drawn from [OpenAI/GSM8K](https://huggingface.co/datasets/openai/gsm8k) (socratic split), filtered to include only samples whose answers contain digits.
2. **DPO Triplet Construction** (English):
- **Prompt**: The math problem
- **Chosen**: The full socratic step-by-step solution
- **Rejected**: The solution stripped of all English letters — leaving only digits, symbols, and whitespace — creating an abstract, vague, uninformative response
3. **Multilingual Translation**: [gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b) (F16 GGUF from [unsloth/gpt-oss-20b-GGUF](https://huggingface.co/unsloth/gpt-oss-20b-GGUF), served with llama.cpp `llama-server` and parallel slots; temperature 0.7, reasoning effort medium) was used to translate the `prompt` and `chosen` columns into 8 languages (100 samples each), with careful instructions to:
- Preserve all mathematical symbols (`$`, `<<>>`, `####`, etc.)
- Add a brief, varying, friendly opening sentence to each solution
- Use context-aware translation (the model receives the original English problem when translating solutions)
4. **English Samples**: The final 100 samples remain in English, with friendly opening sentences added to the solutions by the same model.
**Creation code** is [available here](https://huggingface.co/datasets/mzoelfakar/Mini-GSM8K-Multilingual-Alignment/blob/main/code/Create_dataset.ipynb)
## Language Distribution
| Language | Code | Samples |
|----------|------|---------|
| Arabic | ar | 100 |
| French | fr | 100 |
| Spanish | es | 100 |
| German | de | 100 |
| Italian | it | 100 |
| Portuguese | pt | 100 |
| Chinese | zh | 100 |
| Russian | ru | 100 |
| English | en | 100 |
| **Total** | | **900** |
## Schema
| Column | Type | Description |
|--------|------|-------------|
| `prompt` | string | Math problem (translated to target language) |
| `chosen` | string | Full step-by-step solution with friendly opener (translated) |
| `rejected` | string | Digits-only stripped version of the original English solution |
| `language` | string | ISO 639-1 language code |
| `prompt_en` | string | Original English GSM8K problem that `prompt` was translated from |
| `chosen_en` | string | Original English GSM8K solution that `chosen` was translated from (without the friendly opener) |
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("mzoelfakar/Mini-GSM8K-Multilingual-Alignment", split="train")
# Filter by language
arabic_samples = dataset.filter(lambda x: x["language"] == "ar")
```
## Creator
Created by **[Mohamed Zoelfakar](https://www.linkedin.com/in/mzoelfakar/)** as part of the [Al-Khwarizmi-3B](https://huggingface.co/mzoelfakar/Al-Khwarizmi-3B) project for advancing multilingual mathematical reasoning in small language models.
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