RAdam
deepnet
| RAdam | deepnet | |
|---|---|---|
| 4 | 1 | |
| 2,520 | 319 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | almost 2 years ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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RAdam
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[D] Why does a sudden increase in accuracy at a specific epoch in these model
Code for https://arxiv.org/abs/1908.03265 found: https://github.com/LiyuanLucasLiu/RAdam
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[D] How to pick a learning rate scheduler?
common practice is to include some type of annealing (cosine, linear, etc.), which makes intuitive sense. for adam/adamw, it's generally a good idea to include a warmup in the lr schedule, as the gradient distribution without the warmup can be distorted, leading to the optimizer being trapped in a bad local min. see this paper. there are also introduced in this paper and subsequent works (radam, ranger, and variants) that don't require a warmup stage to stabilize the gradients. i would say in general, if you're using adam/adamw, include a warmup and some annealing, either linear or cosine. if you're using radam/ranger/variants, you can skip the warmup. how many steps to use for warmup/annealing are probably problem specific, and require some hyperparam tuning to get optimimal results
- Why is my loss choppy?
deepnet
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Neural Network from Scratch
For those interested in simple neural networks to CNN and RNNs implemented with just Numpy (including backprop):
https://github.com/parasdahal/deepnet
What are some alternatives?
ML-Optimizers-JAX - Toy implementations of some popular ML optimizers using Python/JAX
micrograd - A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
AdaBound - An optimizer that trains as fast as Adam and as good as SGD.
ML-From-Scratch - Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
pytorch_warmup - Learning Rate Warmup in PyTorch
NNfSiX - Neural Networks from Scratch in various programming languages
pytorch-optimizer - torch-optimizer -- collection of optimizers for Pytorch
MachineLearning - From linear regression towards neural networks...
DemonRangerOptimizer - Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay
machine.academy - Neural Network training library in C++ and C# with GPU acceleration
Best-Deep-Learning-Optimizers - Collection of the latest, greatest, deep learning optimizers (for Pytorch) - CNN, NLP suitable
deeplearning-notes - Notes for Deep Learning Specialization Courses led by Andrew Ng.