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license: gpl-2.0

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license: gpl-2.0
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# 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.
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