Learning Rate Warmup in PyTorch

Gradient based Hyperparameter Tuning library 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.

Pytorch cyclic cosine decay learning rate scheduler

Automatic learning-rate scheduler

Warmup learning rate wrapper for Pytorch Scheduler

A learning rate recommending and benchmarking tool.

sharpDARTS: Faster and More Accurate Differentiable Architecture Search

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

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

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.

Implementation of fluctuation dissipation relations for automatic learning rate annealing.

Code to reproduce the experiments of ICLR2023-paper: How I Learned to Stop Worrying and Love Retraining

(GECCO2023 Best Paper Nomination) CMA-ES with Learning Rate Adaptation

Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.

ABEL implemented in PyTorch

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.