tensorboard
Logs and views ML training data in TensorBoard using PyTorch SummaryWriter and TensorFlow/Keras callbacks: scalars, images, text, histograms, model graphs, embedding projector, hyperparameter tables, PR curves, and TensorFlow or PyTorch profiler traces. Use when plotting loss and accuracy curves during training, comparing multiple runs in one dashboard, inspecting weight and gradient distributions, projecting embeddings with PCA or t-SNE, tracking hyperparameter experiments, or finding performance bottlenecks in a training loop. Not for hosted experiment tracking with team collaboration; use a dedicated tracking service for that.
- Version
- 1.0.0
- License
- MIT
Pinned to revision df088027ff23, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/tensorboard/SKILL.md
- skills/tensorboard/references/advanced-features.md
- skills/tensorboard/references/integration-examples.md
- skills/tensorboard/references/integrations.md
- skills/tensorboard/references/profiling.md
- skills/tensorboard/references/visualization.md
Every link opens the file at its source, pinned to the revision this page describes.