# EvaluationTracker[[lighteval.logging.evaluation_tracker.EvaluationTracker]]

<div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8">


<docstring><name>class lighteval.logging.evaluation_tracker.EvaluationTracker</name><anchor>lighteval.logging.evaluation_tracker.EvaluationTracker</anchor><source>https://github.com/huggingface/lighteval/blob/vr_1032/src/lighteval/logging/evaluation_tracker.py#L95</source><parameters>[{"name": "output_dir", "val": ": str"}, {"name": "results_path_template", "val": ": str | None = None"}, {"name": "save_details", "val": ": bool = True"}, {"name": "push_to_hub", "val": ": bool = False"}, {"name": "push_to_tensorboard", "val": ": bool = False"}, {"name": "hub_results_org", "val": ": str | None = ''"}, {"name": "tensorboard_metric_prefix", "val": ": str = 'eval'"}, {"name": "public", "val": ": bool = False"}, {"name": "nanotron_run_info", "val": ": GeneralArgs = None"}, {"name": "use_wandb", "val": ": bool = False"}]</parameters><paramsdesc>- **output_dir** (str) -- Local directory to save evaluation results and logs
- **results_path_template** (str, optional) -- Template for results directory structure.
  Example: "{output_dir}/results/{org}_{model}"
- **save_details** (bool, defaults to True) -- Whether to save detailed evaluation records
- **push_to_hub** (bool, defaults to False) -- Whether to push results to HF Hub
- **push_to_tensorboard** (bool, defaults to False) -- Whether to push metrics to TensorBoard
- **hub_results_org** (str, optional) -- HF Hub organization to push results to
- **tensorboard_metric_prefix** (str, defaults to "eval") -- Prefix for TensorBoard metrics
- **public** (bool, defaults to False) -- Whether to make Hub datasets public
- **nanotron_run_info** (GeneralArgs, optional) -- Nanotron model run information
- **use_wandb** (bool, defaults to False) -- Whether to log to Weights & Biases or Trackio if available</paramsdesc><paramgroups>0</paramgroups></docstring>
Tracks and manages evaluation results, metrics, and logging for model evaluations.

The EvaluationTracker coordinates multiple specialized loggers to track different aspects of model evaluation:

- Details Logger (DetailsLogger): Records per-sample evaluation details and predictions
- Metrics Logger (MetricsLogger): Tracks aggregate evaluation metrics and scores
- Versions Logger (VersionsLogger): Records task and dataset versions
- General Config Logger (GeneralConfigLogger): Stores overall evaluation configuration
- Task Config Logger (TaskConfigLogger): Maintains per-task configuration details

The tracker can save results locally and optionally push them to:
- Hugging Face Hub as datasets
- TensorBoard for visualization
- Trackio or Weights & Biases for experiment tracking



<ExampleCodeBlock anchor="lighteval.logging.evaluation_tracker.EvaluationTracker.example">

Example:
```python
tracker = EvaluationTracker(
    output_dir="./eval_results",
    push_to_hub=True,
    hub_results_org="my-org",
    save_details=True
)

# Log evaluation results
tracker.metrics_logger.add_metric("accuracy", 0.85)
tracker.details_logger.add_detail(task_name="qa", prediction="Paris")

# Save all results
tracker.save()
```

</ExampleCodeBlock>



<div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8">


<docstring><name>generate_final_dict</name><anchor>lighteval.logging.evaluation_tracker.EvaluationTracker.generate_final_dict</anchor><source>https://github.com/huggingface/lighteval/blob/vr_1032/src/lighteval/logging/evaluation_tracker.py#L363</source><parameters>[]</parameters><rettype>dict</rettype><retdesc>Dictionary containing all experiment information including config, results, versions, and summaries</retdesc></docstring>
Aggregates and returns all the logger's experiment information in a dictionary.

This function should be used to gather and display said information at the end of an evaluation run.






</div>
<div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8">


<docstring><name>push_to_hub</name><anchor>lighteval.logging.evaluation_tracker.EvaluationTracker.push_to_hub</anchor><source>https://github.com/huggingface/lighteval/blob/vr_1032/src/lighteval/logging/evaluation_tracker.py#L387</source><parameters>[{"name": "date_id", "val": ": str"}, {"name": "details", "val": ": dict"}, {"name": "results_dict", "val": ": dict"}]</parameters></docstring>
Pushes the experiment details (all the model predictions for every step) to the hub.

</div>
<div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8">


<docstring><name>recreate_metadata_card</name><anchor>lighteval.logging.evaluation_tracker.EvaluationTracker.recreate_metadata_card</anchor><source>https://github.com/huggingface/lighteval/blob/vr_1032/src/lighteval/logging/evaluation_tracker.py#L454</source><parameters>[{"name": "repo_id", "val": ": str"}]</parameters><paramsdesc>- **repo_id** (str) -- Details dataset repository path on the hub (`org/dataset`)</paramsdesc><paramgroups>0</paramgroups></docstring>
Fully updates the details repository metadata card for the currently evaluated model




</div>
<div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8">


<docstring><name>save</name><anchor>lighteval.logging.evaluation_tracker.EvaluationTracker.save</anchor><source>https://github.com/huggingface/lighteval/blob/vr_1032/src/lighteval/logging/evaluation_tracker.py#L247</source><parameters>[]</parameters></docstring>
Saves the experiment information and results to files, and to the hub if requested.

</div></div>

<EditOnGithub source="https://github.com/huggingface/lighteval/blob/main/docs/source/package_reference/evaluation_tracker.mdx" />