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---
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title: Tuning Experiments
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---
Tune experiments and edit an experiment's execution details, then execute the tuned experiments on local or remote machines.
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## To Tune an Experiment and Execute it Remotely:
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1. Locate the experiment. Open the experiment's Project page from the Dashboard or the main Projects page.
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* On the Dashboard,
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* Click on an experiment from RECENT EXPERIMENTS
* In RECENT PROJECTS ** >** click on a project card ** >** click experiment
* In RECENT PROJECTS ** >** click **VIEW ALL** ** >** click the project card ** >** click experiment
* On the Projects page, click project card, or the **All projects** card ** >** click experiment
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1. Clone the experiment. In the experiments table:
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1. Click **Clone** , and a **Clone experiment** box will pop up.
1. In the **Project** textbox, select or create a project. To search for another project, start typing the project name.
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To create a new project, type new experiment name and click **Create New** .
1. Enter an optional description.
1. Click **CLONE** .
The cloned experiment's status is now *Draft* .
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1. Edit the experiment. See [modifying experiments ](#modifying-experiments ).
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1. Enqueue the experiment for execution. Right click the experiment ** >** **Enqueue** ** >** Select a queue ** >**
**ENQUEUE** .
The experiment's status becomes *Pending* . When the worker assigned to the queue fetches the Task (experiment), the
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status becomes *Running* . The experiment can now be tracked and its results visualized.
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## Modifying Experiments
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Experiments whose status is *Draft* are editable (see the [user properties ](#user-properties ) exception). In the **ClearML
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Web UI**, edit any of the following
* [Source code ](#source-code )
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* [Output destination for artifacts ](#output-destination )
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* [Base Docker image ](#base-docker-image )
* [Log level ](#log-level )
* [Hyperparameters ](#hyperparameters ) - Parameters, TensorFlow Definitions, command line options, environment variables, and user-defined properties
:::note
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User parameters are editable in any experiment, except experiments whose status is *Published* (read-only).
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:::
* [Configuration objects ](#configuration-objects ) - Task model description
* [Initial weight input model ](#initial-weights-input-model )
* [Output destination for artifacts storage ](#output-destination )
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### Execution Details
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#### Source Code
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Select source code by changing any of the following:
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* Repository, commit (select by ID, tag name, or choose the last commit in the branch), script, and /or working directory.
* Installed Python packages and / or versions - Edit or clear (remove) them all.
* Uncommitted changes - Edit or clear (remove) them all.
**To select different source code:**
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* In the **EXECUTION** tab, hover over a section ** >** **EDIT** or (**DISCARD DIFFS** for **UNCOMMITTED CHANGES** ) ** >**
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edit ** >** **SAVE** .
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#### Base Docker Image
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Select a pre-configured Docker that **ClearML Agent** will use to remotely execute this experiment (see [Building Docker containers ](../clearml_agent.md#exporting-a-task-into-a-standalone-docker-container )).
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**To add, change, or delete a base Docker image:**
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* In **EXECUTION** ** >** **AGENT CONFIGURATION** ** >** **BASE DOCKER IMAGE** ** >** hover ** >** **EDIT** ** >**
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Enter the base Docker image.
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#### Output Destination
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Set an output destination for model checkpoints (snapshots) and other artifacts. Examples of supported types of destinations
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and formats for specifying locations include:
* A shared folder: `/mnt/share/folder`
* S3: `s3://bucket/folder`
* Google Cloud Storage: `gs://bucket-name/folder`
* Azure Storage: `azure://company.blob.core.windows.net/folder/`
**To add, change, or delete an artifact output destination:**
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* In **EXECUTION** ** >** **OUTPUT** > **DESTINATION** ** >** hover ** >** **EDIT** ** >** edit ** >** **SAVE** .
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:::note Set Output Destination for Artifacts
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Also set the output destination for artifacts in code (see the `output_uri` parameter of the
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[`Task.init` ](../references/sdk/task.md#taskinit )
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method), and in the ClearML configuration file
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for all experiments (see [`default_output_uri` ](../configs/clearml_conf.md#config_default_output_uri )
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on the ClearML Configuration Reference page).
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:::
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#### Log Level
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Set a logging level for the experiment (see the standard Python [logging levels ](https://docs.python.org/3/howto/logging.html#logging-levels )).
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**To add, change, or delete a log level:**
* In **EXECUTION** ** >** **OUTPUT** ** >** **LOG LEVEL** ** >** hover ** >** **EDIT** ** >** Enter the log level.
### Configuration
#### Hyperparameters
Add, change, or delete hyperparameters, which are organized in the **ClearML Web UI** in the following sections:
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* **Args** - Command line arguments and all older experiments parameters, except TensorFlow definitions (logged from code,
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`argparse` argument automatic logging).
* **TF_DEFINE** - TensorFlow definitions (from code, TF_DEFINEs automatic logging).
* **General** - Parameter dictionaries (from code, connected to the Task by calling the [Task.connect ](../references/sdk/task.md#connect )
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method).
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* Environment variables - Tracked if the `CLEARML_LOG_ENVIRONMENT` environment variable was set (see this [FAQ ](../faq.md#track-env-vars )).
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* Custom named parameter groups (see the `name` parameter in [Task.connect ](../references/sdk/task.md#connect )).
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**To add, change, or delete hyperparameters:**
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* In the **CONFIGURATION** tab ** >** **HYPER PARAMETERS** > **General** ** >** hover ** >** **EDIT** ** >** add, change,
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or delete keys and /or values ** >** **SAVE** .
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#### User Properties
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User properties allow storing any descriptive information in key-value pair format. They are editable in any experiment,
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except experiments whose status is *Published* (read-only).
**To add, change, or delete user properties:**
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* In **CONFIGURATION** ** >** **USER PROPERTIES** > **Properties** ** >** hover ** >** **EDIT** ** >** add, change, or delete
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keys and /or values ** >** **SAVE** .
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#### Configuration Objects
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**To add, change, or delete the Task model configurations:**
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* In **CONFIGURATION** ** >** **CONFIGURATION OBJECTS** ** >** **GENERAL** ** >** hover ** >** **EDIT** or **CLEAR** (if the
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configuration is not empty).
### Artifacts
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### Initial Weights Input Model
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Edit model configuration and label enumeration, choose a different initial input weight model for the same project or any
other project, or remove the model.
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:::note
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The models are editable in the **MODELS** tab, not the **EXPERIMENTS** tab. Clicking the model name hyperlink shows the
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model in the **MODELS** tab.
:::
**To select a different model:**
1. In **ARTIFACTS** ** >** **Input Model** ** >** Hover and click **EDIT** .
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1. If a model is associated with the experiment, click < img src = "/docs/latest/icons/ico-edit.svg" alt = "Edit Pencil" className = "icon size-md" /> .
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1. In the **SELECT MODEL** dialog, select a model from the current project or any other project.
**To edit a model's configuration or label enumeration:**
1. Click the model name hyperlink. The model details appear in the **MODELS** tab.
1. Edit the model configuration or label enumeration.
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* Model configuration - In the **NETWORK** tab ** >** Hover and click **EDIT** . ** >** CLick **EDIT** or **CLEAR** (to
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remove the configuration).
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Users can also search for the configuration (hover over the configuration textbox, the search box appears) and copy the
configuration to the clipboard (hover and click < img src = "/docs/latest/icons/ico-clipboard.svg" alt = "Copy Clipboard" className = "icon size-md" / > ).
* Label enumeration - In the **LABELS** tab ** >** Hover and click **EDIT** ** >** Add, change, or delete label
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enumeration key-value pairs.
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**To remove a model from an experiment:**
* Hover and click **EDIT** ** >** Click < img src = "/docs/latest/icons/ico-trash.svg" alt = "Trash" className = "icon size-md" />