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Related Questions
- What's the typical range of ideal batch sizes for large-scale language model training?
- How does underbunding affect the optimization of models with large training data sets?
- Does gradient explosion commonly occur at very small or large batch sizes?
- What are common heuristics for batching decisions based on the relationship with explosion?
- Do smaller batch sizes allow better exploration of non-volatile regions in deeper, harder-to-optimize, highly complex models before running too long?
- Can a tiny or giant batch size possibly benefit particular models, provided training schedules are appropriately made?!
- Will gradients become too powerful under these conditions and have implications when the learning of this larger model occurs
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