early-stopping-callback

Name: early-stopping-callback - Agent Skill
Rating: 5.0 (1039 reviews)
Author: jeremylongshore

1,039

MIT

Manage early stopping callback operations. Auto-activating skill for ML Training. Triggers on: early stopping callback, early stopping callback Part of the ML Training skill category. Use when working with early stopping callback functionality. Trigger with phrases like "early stopping callback", "early callback", "early".

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CLI Install

Recommended

Use the skills CLI to install this skill with one command. Auto-detects all installed AI assistants.

Method 1 - skills CLI

npx skills i jeremylongshore/claude-code-plugins-plus-skills/skills/07-ml-training/early-stopping-callback

Method 2 - openskills (supports sync & update)

npx openskills install jeremylongshore/claude-code-plugins-plus-skills

Auto-detects Claude Code, Cursor, Codex CLI, Gemini CLI, and more. One install, works everywhere.

Installation Path

Download and extract to one of the following locations:

~/.claude/skills/early-stopping-callback/

SKILL.md

Skill Instructions

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Claude Sonnet 4.5

$0.20/task

Best for coding tasks

No setup required

Early Stopping Callback

Overview

This skill provides automated assistance for early stopping callback tasks within the ML Training domain.

When to Use

This skill activates automatically when you:

Mention "early stopping callback" in your request
Ask about early stopping callback patterns or best practices
Need help with machine learning training skills covering data preparation, model training, hyperparameter tuning, and experiment tracking.

Instructions

Provides step-by-step guidance for early stopping callback
Follows industry best practices and patterns
Generates production-ready code and configurations
Validates outputs against common standards

Examples

Example: Basic Usage Request: "Help me with early stopping callback" Result: Provides step-by-step guidance and generates appropriate configurations

Prerequisites

Relevant development environment configured
Access to necessary tools and services
Basic understanding of ml training concepts

Output

Generated configurations and code
Best practice recommendations
Validation results

Error Handling

Error	Cause	Solution
Configuration invalid	Missing required fields	Check documentation for required parameters
Tool not found	Dependency not installed	Install required tools per prerequisites
Permission denied	Insufficient access	Verify credentials and permissions

Resources

Official documentation for related tools
Best practices guides
Community examples and tutorials

Part of the ML Training skill category. Tags: ml, training, pytorch, tensorflow, sklearn