karpathy/optim — explained in plain English
Analysis updated 2026-07-18 · repo last pushed 2021-08-19
Train a neural network by repeatedly calling an optimizer to adjust its parameters.
Track training progress by recording error values returned on each update step.
Swap in different optimization methods like SGD without changing your training loop.
Persist optimizer state between runs so training can resume where it left off.
| karpathy/optim | gregorias/nvim-surround-wk | not-manu/filemention.nvim | |
|---|---|---|---|
| Stars | 42 | 35 | 58 |
| Language | Lua | Lua | Lua |
| Last pushed | 2021-08-19 | — | — |
| Maintenance | Dormant | — | — |
| Setup difficulty | moderate | easy | easy |
| Complexity | 3/5 | 1/5 | 2/5 |
| Audience | researcher | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Torch and a working Lua environment.
A collection of optimization algorithms (like SGD) for training machine learning models in Torch, a numerical computing framework written in Lua.
Mainly Lua. The stack also includes Lua, Torch.
Dormant — no commits in 2+ years (last push 2021-08-19).
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.