# Replace "my-experiment" with the name of your experiment which can be found in the Opik UI
evaluate_experiment(experiment_name="my-experiment", scoring_metrics=[hallucination_metric])
```

<Tip>
  The `evaluate_experiment` function can be used to update existing scores for an experiment. If you use a scoring
  metric with the same name as an existing score, the scores will be updated with the new values.
</Tip>

<Note>
  You can also compute experiment-level aggregate metrics when updating experiments using the `experiment_scoring_functions` parameter.
  Learn more about [experiment-level metrics](/evaluation/evaluate_your_llm#computing-experiment-level-metrics).
</Note>

## Example

### Create an experiment

Suppose you are building a chatbot and want to compute the hallucination scores for a set of example conversations. For this you would create a first experiment with the `evaluate` function:

```python
from opik import Opik, track
from opik.evaluation import evaluate
from opik.evaluation.metrics import Hallucination
from opik.integrations.openai import track_openai
import openai