wandb-experiment-tracker

Solid

Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.

AI & Automation 814 stars 53 forks Updated today MIT

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Quality Score: 95/100

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Skill Content

# wandb-experiment-tracker ## Overview Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, artifact versioning, and team collaboration. ## Capabilities - Experiment logging and visualization - Hyperparameter sweep configuration and execution - Artifact versioning and lineage tracking - Table and media logging (images, audio, video) - Team collaboration features - Report generation and sharing - Model registry integration - Custom visualization dashboards ## Target Processes - Model Training Pipeline with Experiment Tracking - Experiment Planning and Hypothesis Testing - Model Evaluation and Validation Framework ## Tools and Libraries - Weights & Biases (wandb) ## Input Schema ```json { "type": "object", "required": ["action"], "properties": { "action": { "type": "string", "enum": ["init", "log", "sweep", "artifact", "alert", "report"], "description": "W&B action to perform" }, "project": { "type": "string", "description": "W&B project name" }, "runConfig": { "type": "object", "properties": { "name": { "type": "string" }, "tags": { "type": "array", "items": { "type": "string" } }, "notes": { "type": "string" }, "config": { "type": "object" } } }, "logData": { "type": "object", "properties": { "metrics": { "type": "object" }, "step": { "type": "integer" }, "commit": { "type": "boolean" } ...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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