Kyleyee/qwen2_5-0.5b-sft-arithmetic
Kyleyee/qwen2_5-0.5b-sft-arithmetic is a 0.5 billion parameter language model, fine-tuned from Qwen/Qwen2.5-0.5B-Instruct. This model specializes in arithmetic tasks, having been trained on the Kyleyee/arithmetic-sft dataset using the TRL framework. It is designed for applications requiring enhanced numerical reasoning and mathematical problem-solving capabilities.
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Model Overview
This model, Kyleyee/qwen2_5-0.5b-sft-arithmetic, is a specialized version of the Qwen2.5-0.5B-Instruct architecture, featuring 0.5 billion parameters and a context length of 131072 tokens. It has been specifically fine-tuned to excel in arithmetic reasoning tasks.
Key Capabilities
- Arithmetic Problem Solving: Enhanced performance on mathematical operations and numerical reasoning due to targeted fine-tuning.
- Instruction Following: Retains the instruction-following capabilities of its base Qwen2.5-0.5B-Instruct model.
Training Details
The model underwent Supervised Fine-Tuning (SFT) using the Kyleyee/arithmetic-sft dataset. The training process leveraged the TRL (Transformer Reinforcement Learning) framework, ensuring a focused optimization for arithmetic tasks. This targeted training approach differentiates it from general-purpose language models of similar size.
Use Cases
This model is particularly well-suited for applications where accurate and efficient arithmetic computation or numerical understanding is critical, such as educational tools, data analysis assistants, or systems requiring basic mathematical problem-solving.