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start: Add a parameters hidden section to experiments to merge params…
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…/metrics into experiments (#3163)

* added a hidden section

* Restyled by prettier (#3164)

Co-authored-by: Restyled.io <[email protected]>

* clarification

* stages -> experiments

* added that

* move example out of parens

* revised for command argument link to --set-param

* replaced "Here is..." with "Example"

Co-authored-by: restyled-io[bot] <32688539+restyled-io[bot]@users.noreply.github.com>
Co-authored-by: Restyled.io <[email protected]>
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Expand Up @@ -120,6 +120,32 @@ Experiment results have been applied to your workspace.

<details>

### ℹ️ More information about (Hyper)parameters

It's pretty common for data science projects to include configuration files that
define adjustable parameters to train a model, adjust model architecture, do
pre-processing, etc. DVC provides a mechanism for experiments to depend on the
specific variables from a file.

By default, DVC assumes that a parameters file named `params.yaml` is available
in your project. DVC parses this file and creates dependencies to the variables
found in it: `model.conv_units` and `train.epochs`. Example:

```yaml
train:
epochs: 10
model:
conv_units: 16
```
When you use `dvc exp run --set-param`, DVC updates the parameters in
`params.yaml` with the values you set in the command line before running the
experiment.

</details>

<details>

### ⚙️ Run multiple experiments in parallel

Instead of running the experiments one-by-one, we can define them to run in a
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