{ "cells": [ { "cell_type": "markdown", "id": "0", "metadata": {}, "source": [ "# Custom Training Phase Tutorial\n", "\n", "Illustrate how to create bespoke phases (warm-up, fine-tuning, evaluation) and plug them into the trainer.\n", "Includes callback orchestration and scheduler considerations.\n" ] }, { "cell_type": "markdown", "id": "1", "metadata": {}, "source": [ "## Scenario\n", "\n", "Describe the business or research question being addressed and why this workflow matters.\n" ] }, { "cell_type": "markdown", "id": "2", "metadata": {}, "source": [ "## Setup\n", "\n", "Outline dataset prep, FeatureSet definitions, and experiment context initialization.\n" ] }, { "cell_type": "markdown", "id": "3", "metadata": {}, "source": [ "## Training\n", "\n", "Demonstrate how to assemble nodes, losses, optimizers, and training phases for this scenario.\n" ] }, { "cell_type": "markdown", "id": "4", "metadata": {}, "source": [ "## Evaluation\n", "\n", "Summarize metrics, qualitative checks, and how to inspect :class:`LossRecord` outputs.\n" ] }, { "cell_type": "markdown", "id": "5", "metadata": {}, "source": [ "## What’s Next\n", "\n", "Link to relevant how-to guides, explanations, or follow-up tutorials.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "name": "python", "version": "3.11" } }, "nbformat": 4, "nbformat_minor": 5 }