## Get a single custom-rubric evaluation

`datasets.custom_evals.get(strcustom_eval_id, CustomEvalGetParams**kwargs)  -> CustomEval`

**get** `/api/v1/datasets/{dataset_id}/custom-evals/{custom_eval_id}`

Get a single custom-rubric evaluation

### Parameters

- `dataset_id: str`

- `custom_eval_id: str`

### Returns

- `class CustomEval: …`

  - `custom_eval_id: str`

  - `dataset_id: str`

  - `status: str`

    pending | running | succeeded | failed

  - `judge_prompt: str`

  - `name: Optional[str]`

  - `score_before: Optional[float]`

    Mean rubric score on the original pairs. Null until the eval succeeds.

  - `score_after: Optional[float]`

    Mean rubric score on the adapted pairs. Null until the eval succeeds.

  - `improvement_percent: Optional[float]`

    Percentage change from score_before to score_after. Null until the eval succeeds.

  - `scored_rows: Optional[int]`

    Rows the judge scored. A rubric score is an average over this sample, not the whole dataset.

  - `error_message: Optional[str]`

  - `created_at: datetime`

  - `completed_at: Optional[datetime]`

### Example

```python
import os
from adaption import Adaption

client = Adaption(
    api_key=os.environ.get("ADAPTION_API_KEY"),  # This is the default and can be omitted
)
custom_eval = client.datasets.custom_evals.get(
    custom_eval_id="custom_eval_id",
    dataset_id="dataset_id",
)
print(custom_eval.custom_eval_id)
```

#### Response

```json
{
  "custom_eval_id": "custom_eval_id",
  "dataset_id": "dataset_id",
  "status": "running",
  "judge_prompt": "judge_prompt",
  "name": "name",
  "score_before": 0,
  "score_after": 0,
  "improvement_percent": 0,
  "scored_rows": 0,
  "error_message": "error_message",
  "created_at": "2019-12-27T18:11:19.117Z",
  "completed_at": "2019-12-27T18:11:19.117Z"
}
```