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Small edits (#621)

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pollfly
2023-07-23 12:11:32 +03:00
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4 changed files with 18 additions and 15 deletions
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6
docs/integrations/hydra.md
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@@ -26,10 +26,10 @@ The agent executes the code with the modifications you made in the UI, even over
Clone your experiment, then modify your Hydra parameters via the UI in one of the following ways:
* Modify the OmegaConf directly:
1. In the experiment’s **CONFIGURATION > HYPERPARAMETERS > HYDRA** section, set `_allow_omegaconf_edit_` to `True`
1. In the experiment’s **CONFIGURATION > CONFIGURATION OBJECTS > OmegaConf** section, modify the OmegaConf values
1. In the experiment’s **CONFIGURATION > HYPERPARAMETERS > HYDRA** section, set `_allow_omegaconf_edit_` to `True`
1. In the experiment’s **CONFIGURATION > CONFIGURATION OBJECTS > OmegaConf** section, modify the OmegaConf values
* Add an experiment hyperparameter:
1. In the experiment’s **CONFIGURATION > HYPERPARAMETERS > HYDRA** section, make sure `_allow_omegaconf_edit_` is set
1. In the experiment’s **CONFIGURATION > HYPERPARAMETERS > HYDRA** section, make sure `_allow_omegaconf_edit_` is set
to `False`
1. In the same section, click `Edit`, which gives you the option to add parameters. Input parameters from the OmegaConf
that you want to modify using dot notation. For example, if your OmegaConf looks like this:

2
docs/integrations/yolov5.md
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@@ -142,7 +142,7 @@ New dataset created id=<dataset-id>
```
### Run Training Using a ClearML Dataset
Now that you have a ClearML dataset, you can very simply use it to train custom YOLOv5 models:
Now that you have a ClearML dataset, you can very simply use it to train custom YOLOv5 models:
```commandline
python train.py --img 640 --batch 16 --epochs 3 --data clearml://<your_dataset_id> --weights yolov5s.pt --cache