| --- |
| 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. |
|
|
