Model Overview

This model, developed by locailabs, is a Gemma 3.1B instruction-tuned variant specifically enhanced for mathematical reasoning. It was created using a unique model merging technique where a version fine-tuned on the MetaMathQA dataset was linearly interpolated with the original base model (α=0.5).

Key Capabilities & Performance

The merging approach aims to improve task-specific gains from fine-tuning while simultaneously retaining the base model's general instruction-following abilities, which can sometimes degrade with pure fine-tuning. Benchmarking results highlight this strategy:

• GSM8K: The merged model achieves 39.58, outperforming both the base (33.66) and the purely fine-tuned (37.15) versions.
• MMLU Redux: Scores 40.53, showing a balanced performance between the base (39.79) and FT (41.02).
• IFEval: Demonstrates a score of 36.41, significantly better than the fine-tuned model's 28.84, indicating better instruction adherence.

Good For

• Applications requiring enhanced mathematical problem-solving capabilities.
• Scenarios where strong instruction following is crucial alongside specialized task performance.
• Developers looking for a compact model with balanced performance across reasoning and general instruction tasks.