## Retrieve Training Dataset

`models.scores.retrieve_training_dataset(strmodel_id, ScoreRetrieveTrainingDatasetParams**kwargs)  -> ScoreRetrieveTrainingDatasetResponse`

**get** `/models/{modelId}/scores/training-dataset`

Get the training dataset scores for the given `modelId`

### Parameters

- `model_id: str`

- `project_id: Optional[str]`

  The projectId used for ownership resource management. Either to assert ownership or to set the owner of the resource(s)

### Returns

- `class ScoreRetrieveTrainingDatasetResponse: …`

  - `details: Details`

    Different components used to compute the final score

    - `asset_couples_captions_distance: List[DetailsAssetCouplesCaptionsDistance]`

      For each couple of assets in the training dataset, the distance between the captions

      - `couple: List[str]`

        The couple of AssetIds (example: ['asset_GTrL3mq4SXWyMxkOHRxlpw', 'asset_6VrLs8nC1DHWCfKGaVne0gBn'])

      - `distance: float`

        The Dice-Sørensen distance between the captions of the assetIds of the couple.

    - `asset_couples_similarity: List[DetailsAssetCouplesSimilarity]`

      For each couple of assets in the training dataset, the similarity between the assets

      - `couple: List[str]`

        The couple of AssetIds (example: ['asset_GTrL3mq4SXWyMxkOHRxlpw', 'asset_6VrLs8nC1DHWCfKGaVne0gBn'])

      - `similarity: float`

        The cosine similarity between the assetIds of the couple.

        The value is a number between -1 and 1. The higher the value, the more similar the assets are to each other

    - `assets_embedding_similarity: List[DetailsAssetsEmbeddingSimilarity]`

      For each asset, the similarity with the model's embedding (excluding the current asset)

      - `asset_id: str`

        The AssetId associated with their similarity (example: "asset_GTrL3mq4SXWyMxkOHRxlpw")

      - `similarity: float`

        The cosine similarity between the assetId and the model's embedding minus the asset's embedding

        The value is a number between -1 and 1. The higher the value, the more similar the asset is to the model's embedding

    - `assets_similarity: DetailsAssetsSimilarity`

      The min, mean, median of the assetsEmbeddingSimilarity

      - `mean: float`

      - `median: float`

      - `min: float`

    - `couples_captions_distance: DetailsCouplesCaptionsDistance`

      The min, mean, median of the assetCouplesCaptionsDistance

      - `mean: float`

      - `median: float`

      - `min: float`

    - `couples_similarity: DetailsCouplesSimilarity`

      The min, mean, median of the assetCouplesSimilarity

      - `mean: float`

      - `median: float`

      - `min: float`

    - `metadata_score: float`

      Takes into account all missing data and warnings to compute a metadata score

  - `model_id: str`

    The model ID (example: "model_eyVcnFJcR92BxBkz7N6g5w")

  - `score: float`

    The training dataset's score for the input modelId

    The score is a number between 0 and 1. The higher the score, the most chance the model has to train well

  - `status: Literal["complete", "incomplete", "unknown"]`

    The status of the training dataset's score

    Details if all the necessary data is present to compute the score

    - `"complete"`

    - `"incomplete"`

    - `"unknown"`

  - `asset_couples_warnings: Optional[List[AssetCouplesWarning]]`

    Present only if their is a warning between the assets of the couples

    - `couple: List[str]`

      The couple of AssetIds (example: ['asset_GTrL3mq4SXWyMxkOHRxlpw', 'asset_6VrLs8nC1DHWCfKGaVne0gBn'])

    - `message: List[Literal["Captions are identical", "Captions are too close", "Empty caption", 6 more]]`

      An indicative message concerning the couple of assets

      - `"Captions are identical"`

      - `"Captions are too close"`

      - `"Empty caption"`

      - `"Missing caption"`

      - `"Missing metadata"`

      - `"Same asset"`

      - `"Similarity is too high"`

      - `"Similarity with other assets is too low"`

      - `"Width and height must be larger than 1024"`

  - `assets_warnings: Optional[List[AssetsWarning]]`

    Present only if the training image assets of the modelId have one or more warnings

    - `asset_id: str`

      The AssetId which has a warning (example: "asset_GTrL3mq4SXWyMxkOHRxlpw")

    - `message: List[Literal["Captions are identical", "Captions are too close", "Empty caption", 6 more]]`

      An indicative message concerning the asset

      - `"Captions are identical"`

      - `"Captions are too close"`

      - `"Empty caption"`

      - `"Missing caption"`

      - `"Missing metadata"`

      - `"Same asset"`

      - `"Similarity is too high"`

      - `"Similarity with other assets is too low"`

      - `"Width and height must be larger than 1024"`

### Example

```python
import os
from scenario_sdk import Scenario

client = Scenario(
    api_key=os.environ.get("SCENARIO_SDK_API_KEY"),  # This is the default and can be omitted
    api_secret=os.environ.get("SCENARIO_SDK_API_SECRET"),  # This is the default and can be omitted
)
response = client.models.scores.retrieve_training_dataset(
    model_id="modelId",
)
print(response.details)
```

#### Response

```json
{
  "details": {
    "assetCouplesCaptionsDistance": [
      {
        "couple": [
          "string",
          "string"
        ],
        "distance": 0
      }
    ],
    "assetCouplesSimilarity": [
      {
        "couple": [
          "string",
          "string"
        ],
        "similarity": -1
      }
    ],
    "assetsEmbeddingSimilarity": [
      {
        "assetId": "assetId",
        "similarity": -1
      }
    ],
    "assetsSimilarity": {
      "mean": -1,
      "median": -1,
      "min": -1
    },
    "couplesCaptionsDistance": {
      "mean": 0,
      "median": 0,
      "min": 0
    },
    "couplesSimilarity": {
      "mean": -1,
      "median": -1,
      "min": -1
    },
    "metadataScore": -1
  },
  "modelId": "modelId",
  "score": 0,
  "status": "complete",
  "assetCouplesWarnings": [
    {
      "couple": [
        "string",
        "string"
      ],
      "message": [
        "Captions are identical"
      ]
    }
  ],
  "assetsWarnings": [
    {
      "assetId": "assetId",
      "message": [
        "Captions are identical"
      ]
    }
  ]
}
```