3LC is a turn-key solution for real-time debugging, diagnosis, and improvement of training data. It allows users to see their dataset through their model’s eyes, find important or inefficient samples, understand what samples work and where the model struggles, and improve the model by weighting data. Key features include dataset versioning (making sparse, non-destructive edits and maintaining a lineage of all changes), experiment tracking (aggregating metrics by sample features to spot hidden trends and tying each run to a specific dataset revision), and integration with existing ML tools like PyTorch, TensorFlow and PyTorch Lightning. 3LC works with data wherever it is, requiring no data upload or movement.
• experiment tracking
• visualization tools
• dataset versioning
• integration with existing ml tools
• per-sample per epoch metrics and data tracking
• model-guided interactive data debugging
• diagnosis and improvement of training data
• real-time debugging
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