---
license: mit
tags:
  - colliderml
  - benchmark
  - particle-physics
  - tracking
pretty_name: ColliderML Benchmark Results
size_categories:
  - n<1K
---

# ColliderML Benchmark Results

Machine-scored leaderboard results for the [ColliderML](https://github.com/OpenDataDetector/ColliderML) benchmark tasks.

## Structure

```
results/
  {task}/
    {username}/
      {predictions_sha256}.json
```

Each JSON file records one scored submission:

| Field | Description |
|---|---|
| `submission_id` | UUID assigned by the backend |
| `task` | Benchmark task name (e.g. `tracking`) |
| `submitter` | HuggingFace username |
| `model_repo_id` | Optional link to the submitter's model repo |
| `submitted_at` | ISO 8601 timestamp |
| `scores` | Dict of metric name → value |
| `credits_earned` | Credits awarded for this submission |
| `is_baseline` | Whether this is a reference baseline |
| `predictions_sha256` | SHA-256 of the submitted parquet |

## Tasks

| Task | Primary metric | Dataset |
|---|---|---|
| `tracking` | TrackML weighted efficiency | `ttbar_pu200` |
| `jets` | Jet classification AUC | `ttbar_pu200` |
| `anomaly` | Anomaly AUROC | mixed |
| `tracking_latency` | Inference latency (ms) | `ttbar_pu200` |
| `tracking_small` | TrackML eff under parameter budget | `ttbar_pu200` |
| `data_loading` | Load throughput (events/s) | `ttbar_pu0` |

## Integration

Results are pushed automatically by the ColliderML backend after each scored submission.
The [ColliderML leaderboard Space](https://huggingface.co/spaces/OpenDataDetector/colliderml-leaderboard)
reads from this dataset to render the public table.

Models that include `.eval_results/colliderml_*.yaml` files link back to this dataset,
so scores appear on model cards automatically.

## Links

- **Library:** [OpenDataDetector/ColliderML](https://github.com/OpenDataDetector/ColliderML)
- **Data:** [CERN/ColliderML-Release-1](https://huggingface.co/datasets/CERN/ColliderML-Release-1)
- **Docs:** [opendatadetector.github.io/ColliderML](https://opendatadetector.github.io/ColliderML/)