analist/deepseek-math-tutor-fine-tuned
The analist/deepseek-math-tutor-fine-tuned model is a fine-tuned version of DeepSeek-R1-Distill-Llama-8B, specifically optimized for mathematics education. It is designed to provide beginner-friendly, step-by-step explanations for mathematical problems. This model leverages LoRA fine-tuning on a math reasoning dataset to excel in pedagogical applications for arithmetic, geometry, analysis, and calculus.
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DeepSeek Math Tutor: Specialized for Education
This model, analist/deepseek-math-tutor-fine-tuned, is a specialized adaptation of the DeepSeek-R1-Distill-Llama-8B base model. Its core purpose is to serve as an educational tool, providing clear and beginner-friendly, step-by-step explanations for a wide range of mathematical problems.
Key Capabilities
- Mathematics Education: Optimized for pedagogical applications across arithmetic, geometry, analysis, and calculus.
- Step-by-Step Explanations: Designed to break down complex math problems into understandable steps.
- Beginner-Friendly: Focuses on clarity and accessibility for users learning mathematics.
Training Details
The model was fine-tuned using LoRA on a dedicated math reasoning dataset comprising 7000 examples. The training utilized the Unsloth framework with an AdamW 8-bit optimizer, a learning rate of 2e-4, and a batch size of 2 (per device) over 60 training steps.
Intended Use Cases
This model is ideal for:
- Educational platforms: Integrating into systems that require detailed math problem explanations.
- Personalized tutoring: Assisting students with understanding mathematical concepts.
- Content generation: Creating explanatory content for math curricula.
Limitations
It is important to note that this model is specifically tuned for mathematics education and may not perform optimally on general-purpose language tasks or other domains. Its strength lies in its specialized ability to explain mathematical concepts to beginners.