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Genue Matrix 8B

Model Overview

Genue Matrix 8B is a specialized reasoning engine designed for algebraic word problems, symbolic logic, and mathematical proofs. It leverages a weighted multi-source training strategy to maximize its logical deduction capabilities in a compact 8B parameter package.

The Breakthrough

This model achieved a record-low training loss of 0.35 on the MathInstruct dataset, a highly competitive benchmark for reasoning models. By utilizing a Cosine Soft-Landing scheduler and TIGER-DNA data weighting, Genue Matrix maintains coherence in complex multi-step derivations where standard 8B models typically experience logic collapse.

Training Details

  • Base Model: Llama 3 8B (via Genue Matrix Prime)
  • Dataset: MathInstruct (2,000 weighted samples of GSM8K, MATH, AQuA, and ProofWiki)
  • Final Training Loss: 0.35
  • Scheduler: Cosine Annealing (for superior convergence)

Performance & Tests

  • Algebraic Reasoning: High (Verified via MathInstruct)
  • Word Problem Logic: High (Sub-0.40 loss convergence)
  • Symbolic Consistency: High

Usage

The model follows the Alpaca instruction format:

### Instruction:
[Your algebraic or logic problem]

### Response:
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