This repo helps to track model Weights, Biases and Gradients during training with loss tracking and gives detailed insight for Classification-Model Evaluation
GPL-3.0 License
Classification Report is a high-level library built on top of Pytorch which utilizes Tensorboard and scikit-learn and can be used for any classification problem. It tracks models Weight, Biases and Gradients during training and generates a detailed evaluation report for the model, all of this can be visualized on Tensorboard giving comphrensive insights. It can also be used for HyperParameter tracking which then can be utilized to compare different experiments.
pip install classification-report
Just open this notebook on colab and view the entire tensorboard visualization. - Simple Mnist Simple Reporting Visualize on colab