𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗲𝗿𝗶𝗼𝗱𝘀 𝗶𝗻 𝗗𝗲𝗲𝗽 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀
Deep neural networks do not learn at a constant speed.
They follow specific stages. Some phases change the model weights rapidly. Other phases show little progress.
Researchers call these Critical Learning Periods.
Understanding these periods helps you train models better.
Key takeaways:
- Learning happens in bursts.
- Certain layers update faster than others.
- Timing your training can save compute costs.
- Identifying these stages helps you spot training failures early.
You should track your loss curves to find these windows.
Stop wasting time on training runs that have already passed their peak learning phase.
Source: https://dev.to/paperium/critical-learning-periods-in-deep-neural-networks-2geg
Optional learning community: https://t.me/GyaanSetuAi