[Docs] Add more FAQs about the chocie of parameters

### Summary

Currently, we have a benchmark of network size in the [FAQ](https://docs.deepmodeling.com/projects/deepmd/en/latest/troubleshooting/howtoset_netsize.html). I think we should choose some typical datasets to test more parameters and benchmark their accuracy and speed (for both CPUs and GPUs).

### Detailed Description

I have several ideas here:

- [ ] `type_one_side`: #2265
- [ ] `precision`: In some (or most) systems, FP64 does not improve accuracy compared to FP32.
- [ ] `activation_function`
- [ ] the type of the descriptor: `se_e2_a`, `se_e2_r`, `se_e3`, `local_frame`
- [ ] `axis_neuron`
- [ ] training steps
- [ ] loss function, i.e., the weight of energy/forces
- [ ] learning rate
- [ ] batch size

### Further Information, Files, and Links

_No response_

Start with the existing network-size benchmark in the linked FAQ and determine which datasets and parameter comparisons are in scope. Done means the FAQ contains reproducible accuracy and CPU/GPU speed results for the selected parameters.

Written by the indexing model from the issue text.