Logging Histograms, Gradients and Activations with Comet
Blog post from Comet
Machine learning teams are increasingly using Comet's SDK to visualize neural network training progress through 3D histograms or ridge plots, which provide insight into the model's weights, gradients, and activations. These visualizations help identify optimization issues, such as approaching a local minima or needing to adjust the learning rate due to large gradient variance. The article illustrates the use of Comet's `log_histogram_3D` method to track these metrics with Tensorflow's Gradient Tape, highlighting the process with a simple two-layer perceptron trained on the MNIST dataset. Comet's platform allows users to store and visualize data in histograms, search and sort them, and employ custom panels to monitor these values over time, offering a comprehensive tool for understanding and improving neural network performance.
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