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language: en
license: mit
library_name: pytorch
tags:
- spiking-neural-network
- neuromorphic
- surrogate-gradient
- benchmark
- catalyst
- ssc
datasets:
- ssc
metrics:
- accuracy
model-index:
- name: Catalyst SSC SNN Benchmark (N3)
results:
- task:
type: audio-classification
name: Spoken Command Classification
dataset:
name: Spiking Speech Commands (SSC)
type: ssc
metrics:
- name: Float Accuracy (N3)
type: accuracy
value: 76.4
---
# Catalyst SSC SNN Benchmark (N3)
Spiking Neural Network for spoken command classification on SSC. Achieves 76.4% with adaptive LIF neurons.
## Model Description
- **Architecture (N3)**: 700 → 1024 (recurrent adLIF) → 512 (adLIF) → 35
- **Neuron model**: Adaptive Leaky Integrate-and-Fire (adLIF) with Symplectic Euler discretization
- **Training**: Surrogate gradient BPTT, fast-sigmoid surrogate (scale=25)
- **Hardware target**: Catalyst N3 neuromorphic processor
## Results
| Metric | Value |
|--------|-------|
| Float accuracy | 76.4% |
| Parameters | 2,313,763 |
## Reproduce
```bash
git clone https://github.com/catalyst-neuromorphic/catalyst-benchmarks.git
cd catalyst-benchmarks
pip install -e .
python ssc/train.py --device cuda:0
```
## Links
- **Benchmark repo**: [catalyst-neuromorphic/catalyst-benchmarks](https://github.com/catalyst-neuromorphic/catalyst-benchmarks)
- **Cloud API**: [catalyst-neuromorphic.com](https://catalyst-neuromorphic.com)
- **N3 paper**: [Zenodo DOI 10.5281/zenodo.18881283](https://zenodo.org/records/18881283)
- **N2 paper**: [Zenodo DOI 10.5281/zenodo.18728256](https://zenodo.org/records/18728256)
- **N1 paper**: [Zenodo DOI 10.5281/zenodo.18727094](https://zenodo.org/records/18727094)
## Citation
```bibtex
@misc{catalyst-benchmarks-2026,
author = {Shulayev Barnes, Henry},
title = {Catalyst Neuromorphic Benchmarks},
year = {2026},
url = {https://github.com/catalyst-neuromorphic/catalyst-benchmarks}
}
```
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