Gradient based Hyperparameter Tuning library in PyTorch

Learning Rate Warmup in PyTorch

optimizer & lr scheduler & loss function collections in PyTorch

Polynomial Learning Rate Decay Scheduler for PyTorch

A guide that integrates Pytorch DistributedDataParallel, Apex, warmup, learning rate scheduler, also mentions the set-up of early-stopping and random seed.

Automatic learning-rate scheduler

Pytorch cyclic cosine decay learning rate scheduler

Warmup learning rate wrapper for Pytorch Scheduler

sharpDARTS: Faster and More Accurate Differentiable Architecture Search

Keras Callback to Automatically Adjust the learning rate when it stops improving

A lightweight but efficient Transformer model for accurate univariate stock price forecasting, designed for real-time trading applications. This project transforms the vanilla Transformer architecture for higher-precision financial time series analysis with minimal computational demands.

End-to-end Image Classification using Deep Learning toolkit for custom image datasets. Features include Pre-Processing, Training with Multiple CNN Architectures and Statistical Inference Tools. Special utilities for RAM optimization, Learning Rate Scheduling, and Detailed Code Comments are included.

A learning rate recommending and benchmarking tool.

Pytorch implementation of arbitrary learning rate and momentum schedules, including the One Cycle Policy

ABEL implemented in PyTorch

Implementation of fluctuation dissipation relations for automatic learning rate annealing.

Master's thesis: Experiments on multistage step size schedulers for first-order optimization in minimax problems

Used different Transformer based and LSTM based models for forecasting rainfall in different areas of Mumbai. Employed different smart training techniques to improve correlation with the true time-series.

Code in MATLAB for 1st order optimization algorithms implemented for elastic net regularized convex objective functions.