> ## Documentation Index
> Fetch the complete documentation index at: https://docs.neuroencoder.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Benchmarks

> Performance across clinical EEG tasks

Frozen linear probes, 5-fold subject-level cross-validation. Balanced accuracy (%).

The first column is **EPI-250k**, our base foundation model — not publicly released. It is the upper bound on what the MRL distillation can preserve. The remaining columns are the MRL model at each truncation dimension, which is what `pip install neuroencoder` gives you.

## Private clinical tasks

40,909 annotated 30-second epochs from the Swiss Epilepsy Center.

| Task                   | EPI-250k |  768 |  384 |  192 |  48  |  16  |
| ---------------------- | :------: | :--: | :--: | :--: | :--: | :--: |
| Seizure / Wake         | **93.4** | 93.1 | 92.7 | 92.5 | 91.5 | 84.1 |
| Sleep (5-class)        | **85.1** | 77.0 | 77.4 | 76.9 | 76.5 | 73.2 |
| Artifact / Wake        | **90.2** | 90.5 | 90.3 | 90.5 | 90.7 | 65.9 |
| Seizure / Sleep        | **88.8** | 85.2 | 84.9 | 84.0 | 82.1 | 79.4 |
| Spike / Seizure        | **81.5** | 76.2 | 75.9 | 74.7 | 71.0 | 65.5 |
| Spike / Wake           | **97.0** | 94.8 | 94.7 | 94.6 | 92.9 | 87.2 |
| Artifact / Spike       | **78.8** | 76.0 | 75.6 | 75.3 | 74.4 | 70.4 |
| Category (6-cls)       | **36.3** | 33.6 | 33.3 | 32.8 | 31.7 | 27.4 |
| Clinical Sub (7-cls)   | **42.7** | 31.4 | 31.4 | 31.4 | 27.0 | 23.7 |
| All Sublabels (49-cls) | **22.1** | 14.8 | 14.4 | 13.7 | 12.3 | 10.6 |

## Public benchmarks

10 standard public EEG datasets, evaluated under identical conditions.

| Task       | EPI-250k |  768 |  384 |  192 |  48  |  16  |
| ---------- | :------: | :--: | :--: | :--: | :--: | :--: |
| TUAB       | **73.1** | 72.4 | 72.5 | 72.9 | 72.2 | 70.4 |
| TUEV       | **54.5** | 45.9 | 47.2 | 46.7 | 42.8 | 32.1 |
| TUAR       | **45.2** | 43.0 | 42.9 | 42.2 | 39.5 | 36.5 |
| TUSL       | **73.3** | 71.5 | 75.1 | 77.1 | 71.3 | 69.7 |
| Mumtaz     | **82.1** | 80.7 | 81.8 | 82.6 | 83.2 | 83.1 |
| Schizo     | **71.1** | 70.1 | 69.4 | 69.5 | 69.4 | 66.7 |
| MentArith  | **60.9** | 60.2 | 59.9 | 58.6 | 55.6 | 52.2 |
| ADFTD      | **43.2** | 40.0 | 40.0 | 41.0 | 38.6 | 35.9 |
| PhysioMI   | **30.3** | 28.3 | 28.4 | 27.3 | 27.7 | 25.2 |
| Parkinsons | **62.9** | 58.9 | 58.6 | 58.2 | 55.9 | 53.2 |

The numeric column headers (`768`, `384`, ...) are the MRL truncation dimensions.

## Dimension retention

Mean delta vs the EPI-250k base model, across all 20 tasks.

| MRL dim | Mean delta |
| :-----: | :--------: |
|   768   |   -3.4 pp  |
|   384   |   -3.3 pp  |
|   192   |   -3.5 pp  |
|    48   |   -5.3 pp  |
|    16   |  -10.0 pp  |

Binary tasks retain accuracy best. Fine-grained multi-class tasks (TUEV, sublabels) and tasks with large domain shift from pre-training data (Parkinsons, MI) degrade more sharply.