# Run the evaluation
evaluation_results = evaluate(
    experiment_name="gretel-qa-evaluation",
    dataset=opik_data,
    task=evaluation_task,
    scoring_metrics=[hallucination_metric],
)
```

## Dataset Size Requirements

| Dataset Size       | Holdout Setting         | Example                                                       |
| ------------------ | ----------------------- | ------------------------------------------------------------- |
| **\< 200 records** | `holdout=None`          | `from_data_source(df, holdout=None)`                          |
| **200+ records**   | Default (5%) or custom  | `from_data_source(df)` or `from_data_source(df, holdout=0.1)` |
| **Large datasets** | Custom percentage/count | `from_data_source(df, holdout=250)`                           |

## When to Use Which Approach?

| Use Case                               | Recommended Approach | Why                                                  |
| -------------------------------------- | -------------------- | ---------------------------------------------------- |
| **Creating new datasets from scratch** | **Data Designer**    | More control, custom column types, guided generation |
| **Synthesizing existing datasets**     | **Safe Synthetics**  | Preserves statistical relationships, privacy-safe    |
| **Custom data structures**             | **Data Designer**    | Flexible column definitions, template system         |
| **Production data replication**        | **Safe Synthetics**  | Maintains data utility while ensuring privacy        |

## Environment Variables

Make sure to set the following environment variables:

```bash