wandb-tracker

What problem does it solve?

This Skill streamlines the process of tracking machine learning experiments, ensuring reproducibility, and facilitating easy comparison of training runs and hyperparameter tuning results.

Core Features & Use Cases

• Experiment Tracking: Log metrics, hyperparameters, and artifacts for ML training runs.
• Artifact Versioning: Version control for model checkpoints, tokenizers, and datasets.
• Hyperparameter Tuning: Facilitates side-by-side comparison of runs to identify optimal configurations.
• Use Case: When training a new deep learning model, use this skill to automatically log training/validation loss, learning rate, and GPU utilization to Weights & Biases, allowing you to visualize progress and compare different model architectures.

Quick Start

Use the wandb-tracker skill to initialize a new W&B run for the 'image-classification' project with the entity 'my-org'.