| --- |
| library_name: transformers |
| license: apache-2.0 |
| license_link: https://huggingface.co/Intel/hebrew-math-tutor-v1/blob/main/LICENSE |
| pipeline_tag: text-generation |
| language: |
| - he |
| - en |
| tags: |
| - mathematics |
| - education |
| - hebrew |
| - reasoning |
| - math |
| - tutoring |
| base_model: |
| - Qwen/Qwen3-4B-Thinking-2507 |
| --- |
| |
| # Hebrew Math Tutor |
|
|
| <p align="center"> |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/62d93cd728f9c86a4031562e/YxvxPWRpINziJaAftl4XE.png" width="600"/> |
| </p> |
|
|
| **Hebrew Math Tutor** is a specialized mathematical reasoning model that provides step-by-step solutions to math problems in Hebrew. Built on Qwen3-4B-Thinking-2507, this model bridges the gap between advanced AI mathematical capabilities and Hebrew-language education. |
|
|
|
|
| - ๐ฏ **Model ID**: `Intel/hebrew-math-tutor-v1` |
| - ๐ค **Demo**: [IntelLabs/hebrew-math-tutor](https://huggingface.co/spaces/IntelLabs/hebrew-math-tutor) |
| - ๐ **Blog**: [Hugging Face blog](https://huggingface.co/blog/danf/hebrew-math-tutor) |
| - ๐๏ธ **Base Model**: [Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) |
| - ๐๏ธ **Architecture**: Decoder-only causal language model (~4B parameters) |
| - ๐ฃ๏ธ **Primary Language**: Hebrew (retains multilingual capabilities) |
| - ๐ **License**: Apache-2.0 |
|
|
|
|
| ## Model Description |
|
|
| Hebrew Math Tutor is a supervised fine-tune of Qwen3-4B-Thinking, specifically optimized to: |
|
|
| - **Provide detailed mathematical reasoning in Hebrew** with clear step-by-step explanations |
| - **Maintain mathematical accuracy** while adapting to Hebrew language patterns |
| - **Preserve multilingual capabilities** for cross-language mathematical workflows |
| - **Support educational applications** with natural Hebrew mathematical discourse |
|
|
| The model excels at translating complex mathematical concepts into clear, pedagogically sound Hebrew explanations while maintaining the computational precision of its base model. |
|
|
| ## Intended Use Cases |
|
|
| ### โ
**Primary Applications** |
|
|
| - **Educational Technology**: Hebrew-language math tutoring systems and learning platforms. |
| - **Research Tools**: Mathematical reasoning research in Hebrew educational contexts. |
| - **Prototype Development**: Building Hebrew-first educational AI applications. |
| - **Accessibility**: Providing advanced math AI assistance to Hebrew-speaking communities. |
|
|
| ### โ
**Secondary Applications** |
|
|
| - Multilingual educational workflows requiring Hebrew mathematical explanations. |
| - Cross-cultural mathematics education research. |
| - Hebrew mathematical content generation for educational materials. |
|
|
| ### โ **Not Intended For** |
|
|
| - **High-stakes assessments**: Medical, legal, or financial decision-making. |
| - **Unsupervised grading**: Certification or evaluation without human verification. |
| - **Production systems**: Critical applications without proper validation and oversight. |
|
|
| ## Model Details |
|
|
| | **Specification** | **Details** | |
| |-----------------------|--------------------------------------------------| |
| | **Architecture** | Decoder-only transformer (causal language model) | |
| | **Parameters** | ~4 billion | |
| | **Context Length** | Inherited from Qwen3-4B-Thinking-2507 | |
| | **Tokenizer** | Qwen3-compatible tokenizer with Hebrew support | |
| | **Training Type** | Supervised Fine-Tuning (Hebrew SFT) | |
| | **Base Model** | Qwen3-4B-Thinking-2507 | |
| | **Fine-tuning Focus** | Mathematical reasoning in Hebrew | |
|
|
| ## Training Details |
|
|
| ### **Dataset** |
|
|
| - **Source**: ~10,000 selected problems from [OpenMathReasoning](https://huggingface.co/datasets/nvidia/OpenMathReasoning). |
| - **Translation Approach**: Automated high-quality translation using internal LLMs. |
| - **Language Adaptation**: Questions and final answers translated to Hebrew; reasoning chains preserved. |
| - **Mathematical Notation**: Equations and formal math notation kept intact. |
| - **Internal Reasoning**: Model's `<think>...</think>` blocks intentionally remain in English (representing internal reasoning processes). |
|
|
| ### **Training Configuration** |
|
|
| - **Method**: Supervised Fine-Tuning (Hebrew SFT) |
| - **Epochs**: 3 |
| - **Learning Rate**: 5e-6 |
| - **Warmup**: 0.1 |
| - **Scheduler**: Cosine learning rate decay |
| - **Objective**: Maintain mathematical accuracy while adapting output to Hebrew |
|
|
| ## Performance Evaluation |
|
|
| We evaluated Hebrew Math Tutor on three challenging mathematical benchmarks: **MATH500**, **AIME24**, and **AIME25**. |
|
|
| ### **Evaluation Metrics** |
|
|
| - **pass@16**: Percentage of problems where at least one of 16 generated samples is correct. |
| - **maj@16**: Majority-vote accuracy across 16 samples. |
| - **Hebrew Answers**: Percentage of responses generated in Hebrew. |
|
|
| ### **Hebrew Evaluation Results** |
|
|
| | Dataset | Metric | Base Model | Hebrew Math Tutor | Improvement | |
| |-------------|----------------|------------|-------------------|-------------| |
| | **MATH500** | pass@16 | 93% | **95%** | +2% | |
| | | maj@16 | 88% | **90%** | +2% | |
| | | Hebrew Answers | 75% | **100%** | +25% | |
| | **AIME24** | pass@16 | 76.7% | **80%** | +3.3% | |
| | | maj@16 | 76.7% | **76.7%** | No change | |
| | | Hebrew Answers | 35.2% | **96.7%** | +61.5% | |
| | **AIME25** | pass@16 | 80% | **83.3%** | +3.3% | |
| | | maj@16 | 70% | **60%** | -10% | |
| | | Hebrew Answers | 36% | **95.2%** | +59.2% | |
|
|
| ### **English/Original Language Results** |
|
|
| | Dataset | Metric | Base Model | Hebrew Math Tutor | Change | |
| |-------------|---------|------------|-------------------|-----------| |
| | **MATH500** | pass@16 | 99% | **98%** | -1% | |
| | | maj@16 | 98% | **98%** | No change | |
| | **AIME24** | pass@16 | 93.3% | **90%** | -3.3% | |
| | | maj@16 | 86.7% | **86.7%** | No change | |
| | **AIME25** | pass@16 | 83.3% | **90%** | +6.7% | |
| | | maj@16 | 73% | **80%** | +7% | |
|
|
| ### **Key Findings** |
|
|
| ๐ฏ **Dramatic Language Improvement**: Hebrew answer generation increased by 25-61.5% across all benchmarks, reaching 95-100% Hebrew output. |
|
|
| ๐ **Maintained Technical Performance**: Consistent improvements in pass@16 on Hebrew evaluations while preserving competitive English performance. |
|
|
| ๐ **Mixed Majority Vote Results**: Strong performance on MATH500, stable on AIME24, with one notable decrease on AIME25 requiring further investigation. |
|
|
| โ
**Preserved Core Capabilities**: The fine-tuning successfully adapted language output without sacrificing fundamental mathematical reasoning abilities. |
|
|
| ## Usage |
|
|
| ### **Quick Start** |
|
|
| ```python |
| from transformers import pipeline |
| |
| model = "Intel/hebrew-math-tutor-v1" |
| pipe = pipeline("text-generation", model) |
| |
| messages = [ |
| { |
| "role": "system", |
| "content": """You are a helpful AI assistant specialized in mathematics and problem-solving who can answer math questions with the correct answer. |
| Answer shortly, not more than 500 tokens, but outline the process step by step. |
| Answer ONLY in Hebrew!""", |
| }, |
| {"role": "user", "content": "ืืื ืกืืื ืืกืืจื ืืืื: 1 + 1/2 + 1/4 + 1/8 + ..."}, |
| ] |
| |
| out = pipe( |
| messages, |
| return_full_text=False, |
| max_new_tokens=1024, |
| temperature=0.6, |
| top_p=0.95, |
| top_k=20, |
| ) |
| print(out[0]["generated_text"]) |
| ``` |
|
|
| ### **Recommended Parameters** |
|
|
| - **Temperature**: 0.6 (balanced creativity and accuracy) |
| - **Top-p**: 0.95 (diverse but focused sampling) |
| - **Top-k**: 20 (controlled vocabulary selection) |
| - **Max tokens**: 500-1024 (sufficient for detailed explanations) |
|
|
| ### **Best Practices** |
|
|
| - **Request explicit structure**: Ask for step-by-step reasoning and clearly marked final answers. |
| - **Use Hebrew formatting cues**: Include phrases like "ืชืฉืืื ืกืืคืืช:" or request `\boxed{}` formatting. |
| - **Specify language**: Explicitly request Hebrew-only responses for consistent output. |
| - **Verify solutions**: Always validate mathematical results, especially in educational contexts. |
|
|
| ## Demo Interface |
|
|
| <p align="center"> |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/62d93cd728f9c86a4031562e/tbOIu47QLmja_z-Ce20a2.png" width="600"/> |
| <br> |
| <em>Example Streamlit interface showing Hebrew Math Tutor providing step-by-step reasoning. The detailed reasoning can be collapsed for cleaner presentation.</em> |
| </p> |
| |
| ## Limitations & Considerations |
|
|
| ### **Technical Limitations** |
|
|
| - **Potential errors**: May produce incorrect solutions or mathematical hallucinations. |
| - **Language mixing**: Occasional mixing of Hebrew and English or inconsistent number formatting. |
| - **Training biases**: May reflect biases present in the original training datasets. |
| - **Internal reasoning**: `<think>...</think>` blocks remain in English due to training scope. |
|
|
| ### **Usage Recommendations** |
|
|
| - **Human verification required**: Always validate outputs before use in educational settings |
| - **Not a replacement for educators**: Designed as an assistive tool, not a substitute for qualified instruction. |
| - **Appropriate context**: Best suited for educational prototyping and research applications. |
|
|
| ## Ethical Guidelines |
|
|
| ### **Responsible Deployment** |
|
|
| - Include clear disclaimers about AI-generated content in user-facing applications. |
| - Implement human oversight for any educational or assessment applications. |
| - Ensure compliance with relevant privacy laws when collecting user data. |
| - Provide transparency about model capabilities and limitations. |
|
|
| ### **Educational Impact** |
|
|
| - Designed to enhance, not replace, human mathematical instruction. |
| - Intended to increase accessibility of advanced math AI for Hebrew speakers. |
| - Should be used as part of comprehensive educational approaches with human guidance. |
|
|
| ## Technical Details |
|
|
| ### **Evaluation Methodology** |
|
|
| - **Correctness verification**: Solutions validated using Math-verify framework. |
| - **Statistical significance**: Results based on 16 samples per problem for robust evaluation. |
| - **Language detection**: Automated classification of response language for Hebrew Answers metric. |
| - **Benchmark diversity**: Evaluation across competition mathematics (AIME) and curriculum problems (MATH500). |
|
|
| ### **Reproducibility** |
|
|
| - All evaluation protocols follow standard mathematical reasoning assessment practices. |
| - Sampling parameters and evaluation metrics clearly documented. |
| - Training configuration and hyperparameters provided for reproduction. |
|
|
| ## Attribution & Licensing |
|
|
| - **Model License**: [Apache-2.0](https://huggingface.co/Intel/hebrew-math-tutor-v1/blob/main/LICENSE) |
| - **Base Model**: [Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) (Alibaba) |
| - **Training Dataset**: [OpenMathReasoning](https://huggingface.co/datasets/nvidia/OpenMathReasoning) (NVIDIA) |
| - **Development**: Intel Labs |
|
|
| ## Citation |
|
|
| If you use Hebrew Math Tutor in your research or applications, please cite: |
|
|
| ```bibtex |
| @misc{hebrew-math-tutor-v1, |
| title={Hebrew Math Tutor: A Hebrew-focused Mathematical Reasoning Model}, |
| author={Intel AI}, |
| year={2025}, |
| url={https://huggingface.co/Intel/hebrew-math-tutor-v1}, |
| note={Fine-tuned from Qwen3-4B-Thinking-2507} |
| } |
| ``` |
|
|
| ## Community & Support |
|
|
| - **Blog Post**: [more details in the blog](https://huggingface.co/blog/danf/hebrew-math-tutor). |
| - **Model Repository**: [https://huggingface.co/Intel/hebrew-math-tutor-v1](https://huggingface.co/Intel/hebrew-math-tutor-v1) |
| - **Issues & Feedback**: Use the Hugging Face repository issues for bug reports and feature requests. |
| - **Community Discussions**: Join conversations in the repository discussions tab. |
|
|
| ## Changelog |
|
|
| - **v1.0** โ Initial public release with Hebrew mathematical reasoning capabilities. |
|
|
| --- |
|
|
| *Hebrew Math Tutor represents a step forward in making advanced mathematical AI accessible across languages. We encourage responsible use and welcome community feedback to improve multilingual mathematical reasoning capabilities.* |
