Axelerate/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-flexible_bold_butterfly
Axelerate/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-flexible_bold_butterfly is a fine-tuned instruction-following language model based on Gensyn's Qwen2.5-0.5B-Instruct. This model has been specifically trained using the GRPO method, which is designed to enhance mathematical reasoning capabilities. It is suitable for tasks requiring improved logical and mathematical problem-solving, building upon the base Qwen2.5 architecture.
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Overview
This model, Axelerate/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-flexible_bold_butterfly, is an instruction-tuned variant of the Gensyn/Qwen2.5-0.5B-Instruct base model. It has been fine-tuned using the TRL library and incorporates the GRPO (Gradient-based Reward Policy Optimization) training method. The GRPO method, detailed in the paper "DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models," suggests an optimization for tasks requiring robust mathematical and logical reasoning.
Key Capabilities
- Instruction Following: Inherits and refines the instruction-following abilities of the Qwen2.5-Instruct series.
- Enhanced Reasoning: Benefits from GRPO training, which is associated with improved mathematical reasoning in language models.
Training Details
The model was trained with specific versions of key frameworks:
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
Good For
- Applications requiring a compact instruction-tuned model with a focus on logical or mathematical problem-solving.
- Scenarios where the base Qwen2.5-0.5B-Instruct model's reasoning capabilities need a boost through specialized fine-tuning.