MathCoder-7B: Instruction-Tuned Educational Math Model
Overview
MathCoder-7B is a fine-tuned large language model designed to generate clear, step-by-step solutions for educational mathematics problems. The model focuses on instructional clarity and reasoning transparency rather than benchmark optimisation.
Task
- Educational math problem solving
- Step-by-step solution generation
- Math tutoring assistance
Training Details
- Base model: 7B parameter open-source language model
- Fine-tuning approach: Instruction tuning
- Dataset: Custom-curated educational math instruction data
- Training environment: Single-GPU setup
- Objective: Improve structured reasoning and explanation quality
Intended Use
This model is intended for academic research, educational tools, and experimentation with math tutoring systems. It is not designed for production use or safety-critical applications.
Limitations
- The model has not been evaluated on standard mathematical benchmarks.
- It may generate verbose outputs for simple problems.
- Errors may occur for advanced or highly specialised math topics.
Notes
- This model was developed as part of MSc-level academic coursework.
- Emphasis was placed on clarity of reasoning and pedagogical usefulness.
- Future work may include dataset expansion and formal evaluation.
Changelog
- August 2025: Initial fine-tuned release
- Planned: Improved dataset and evaluation in future versions
Example Usage
from transformers import pipeline
pipe = pipeline("text-generation", model="ushasree2001/math_coder")
pipe("Solve: If 3x + 5 = 14, find x.")
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