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dl-transformer-finetune

Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows.

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Overview

Skill Key
0x-professor/dl-transformer-finetune
Author
0x-professor
Source Repo
openclaw/skills
Version
-
Source Path
skills/0x-professor/dl-transformer-finetune
Latest Commit SHA
45e7379c5ada58d3430d4bf810b53b7060456e84

Extracted Content

SKILL.md excerpt

# DL Transformer Finetune

## Overview

Generate reproducible fine-tuning run plans for transformer models and downstream tasks.

## Workflow

1. Define base model, task type, and dataset.
2. Set training hyperparameters and evaluation cadence.
3. Produce run plan plus model card skeleton.
4. Export configuration-ready artifacts for training pipelines.

## Use Bundled Resources

- Run `scripts/build_finetune_plan.py` for deterministic plan output.
- Read `references/finetune-guide.md` for hyperparameter baseline guidance.

## Guardrails

- Keep run plans reproducible with explicit seeds and output directories.
- Include evaluation and rollback criteria.

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