ckryu84/gemma-3-1b-it-Math-SFT-RS-DPO
The ckryu84/gemma-3-1b-it-Math-SFT-RS-DPO is a 1 billion parameter instruction-tuned Gemma model, developed by ckryu84, with a context length of 32768 tokens. This model is specifically fine-tuned for mathematical tasks, leveraging Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RS-DPO). It is designed to excel in mathematical reasoning and problem-solving applications.
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Model Overview
This model, ckryu84/gemma-3-1b-it-Math-SFT-RS-DPO, is a 1 billion parameter instruction-tuned variant of the Gemma architecture. It features an extended context length of 32768 tokens, making it suitable for processing longer mathematical problems or complex instructions.
Key Characteristics
- Architecture: Based on the Gemma family of models.
- Parameter Count: 1 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports up to 32768 tokens, enabling the model to handle extensive input sequences.
- Fine-tuning: Utilizes Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RS-DPO) specifically for mathematical tasks.
Intended Use Cases
This model is primarily designed for applications requiring strong mathematical reasoning and problem-solving capabilities. It is particularly well-suited for:
- Solving mathematical equations and word problems.
- Assisting with mathematical proofs and derivations.
- Generating explanations for mathematical concepts.
Limitations
As indicated by the model card, specific details regarding training data, evaluation results, biases, risks, and environmental impact are currently marked as "More Information Needed." Users should exercise caution and conduct their own evaluations for critical applications.