Comet ❤️ Hugging Face
Get started with auto-logging model metrics and parameters to Comet from the Hugging Face transformers library.
Logging Histograms, Gradients and Activations with Comet
Introduction 3D Histograms or Ridge Plots are a great way to visualize the training progress of your Neural Network. Histogram…
Debugging Classifiers with Confusion Matrices
A confusion matrix can provide us with a more representative view of our classifier’s performance, including which specific instances it is having trouble classifying.
Introducing Panels: Custom Visualizations for Machine Learning
In the last three years since Comet was founded, our users and customers trained millions of models on anything from…
Predictive Early Stopping – A Meta Learning Approach
Introduction Model training is arguably the most time consuming, and computationally demanding part of the Machine Learning pipeline. Depending on…
Estimating Uncertainty in Machine Learning Models — Part 3
Check out part 1 (here)and part 2 (here) of this series In the last part of our series on…
Estimating Uncertainty in Machine Learning Models – Part 2
You can check out part 1 of this series here In part 1 of this series, we discussed the sources…
