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Parameter Golf Auxiliary Dataset (PG-CCE)

This dataset is designed to reduce entropy in language models by addressing three critical failure modes:

  1. Hallucination / uncertainty calibration
  2. Long-context consistency and state tracking
  3. Exact discrete reasoning (numbers, code, structured patterns)

It is intended as a small auxiliary training dataset to improve bits-per-byte (BPB) performance in Parameter Golf.

Usage

Mix as auxiliary data:

  • 97% main dataset (FineWeb)
  • 3% PG-CCE

Do not replace the main dataset.

Structure

Each record contains:

  • task
  • input
  • target

Goal

Reduce probability mass on incorrect but plausible outputs and improve structural precision.

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