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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---
name: dl-transformer-finetune
description: "Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows."
---
# 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.
