CS5720 - Week 9
Slide 176 of 180

TensorBoard: Visualizing Training

TensorBoard Overview

TensorBoard is a powerful visualization toolkit that provides insights into your model's training process, architecture, and performance through interactive web-based dashboards.
🚀
Quick Setup
Easy integration with PyTorch training loops
⚡
Real-time Updates
Live monitoring during training
🎮
Interactive Plots
Zoom, pan, and explore your data
📤
Easy Sharing
Share results with team members

Visualization Types

  • 📈
    Scalars
    Plot loss, accuracy, and other metrics over time
  • 📊
    Histograms
    Visualize weight and gradient distributions
  • 🖼️
    Images
    Display input data, feature maps, and predictions
  • 🕸️
    Graphs
    Explore model architecture and computation flow
  • 🎯
    Embeddings
    Visualize high-dimensional data in 2D/3D space

TensorBoard in Action

Setup & Usage
Live Examples
Advanced Features
💿
Installation
Install and configure TensorBoard
📝
Basic Logging
Log metrics in your training loop
🚀
Launch TensorBoard
Start the web interface
📈
Training Curves
Loss and accuracy visualization
🕸️
Model Graph
Neural network architecture
📊
Weight Distributions
Parameter evolution over time
⚙️
Hyperparameter Tuning
Compare different configurations
🎯
Embedding Projector
Explore high-dimensional embeddings
⏱️
Performance Profiling
Optimize training performance
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Prepared by Dr. Gorkem Kar