leibnitz-lab/colinear_scaling_models

license: gpl-2.0

Collinear Scaling Models

Checkpoint repository for scaling law experiments comparing collinear (CO) and non-collinear (NC) experimental designs.

Directory Structure

{dataset}/{design}/N_{param_count}/

• Dataset: wikipedia, pes2o, cosmopedia, redpajama, c4 (plus _fp16 and _bigtpp variants)
• Design: colinear or non_colinear
• N: Model parameter count (one of 14 canonical sizes from ~5M to ~70M)

Experimental Designs

Collinear (CO): Models are trained along a line in (N, D) space where D = TPP × N for varying TPP (tokens per parameter) values. A single model size N is swept across many TPP values.

Non-collinear (NC): Models are trained on a grid over (N, D) space (NxD_GRID), varying both N and D independently.

Holdout Sets

Some checkpoints include HOLDOUT in the filename. These were held out from scaling law fitting and are used to evaluate extrapolation / interpolation accuracy of fitted scaling laws. Both CO and NC designs have holdout checkpoints:

• COLINEAR_HOLDOUT_* → collinear holdout (held-out TPP values)
• *_HOLDOUT_* (without COLINEAR) → non-collinear holdout (held-out (N, D) pairs)

Filename Convention

{PREFIX}{DESIGN}N{approx_size}[TPP{val}]D{tokens}_{dataset}_m{exact_N}_token{exact_D}lr{lr}..._completedAt{timestamp}.pt

The m{N} and token{D} fields contain the exact parameter count and token count used for training.