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README.md

@@ -14,7 +14,7 @@ datasets:
 metrics:
   - accuracy
 model-index:
-  - name: Catalyst SHD SNN Benchmark (N3)
+  - name: Catalyst SHD SNN Benchmark
     results:
       - task:
           type: audio-classification
@@ -26,25 +26,37 @@ model-index:
           - name: Float Accuracy (N3)
             type: accuracy
             value: 91.0
+          - name: Float Accuracy (N2)
+            type: accuracy
+            value: 84.5
+          - name: Float Accuracy (N1)
+            type: accuracy
+            value: 90.6
+          - name: Quantised Accuracy (N3, int16)
+            type: accuracy
+            value: 90.8
 ---
 
-# Catalyst SHD SNN Benchmark (N3)
+# Catalyst SHD SNN Benchmark
 
-Spiking Neural Network for spoken digit classification on SHD. Achieves 91.0% with adaptive LIF neurons.
+Spiking Neural Network trained on the Spiking Heidelberg Digits (SHD) dataset using surrogate gradient BPTT. Achieves 91.0% on SHD with adaptive LIF neurons (90.8% quantised int16).
 
 ## Model Description
 
 - **Architecture (N3)**: 700 → 1536 (recurrent adLIF) → 20
+- **Architecture (N2)**: 700 → 512 (recurrent adLIF) → 20
+- **Architecture (N1)**: 700 → 1024 (recurrent LIF) → 20
 - **Neuron model**: Adaptive Leaky Integrate-and-Fire (adLIF) with learnable per-neuron thresholds
-- **Training**: Surrogate gradient BPTT, fast-sigmoid surrogate (scale=25)
-- **Hardware target**: Catalyst N3 neuromorphic processor
+- **Training**: Surrogate gradient BPTT, fast-sigmoid surrogate (scale=25), cosine LR scheduling
+- **Hardware target**: Catalyst N1/N2/N3 neuromorphic processors
 
 ## Results
 
-| Metric | Value |
-|--------|-------|
-| Float accuracy | 91.0% |
-| Parameters | 3,470,484 |
+| Generation | Architecture | Float Accuracy | Params | vs SOTA |
+|------------|-------------|----------------|--------|---------|
+| **N3** | 700→1536→20 (rec, adLIF) | **91.0%** | 3.47M | Matches Loihi 2 (90.9%) |
+| N2 | 700→512→20 (rec, adLIF) | 84.5% | 759K | — |
+| N1 | 700→1024→20 (rec, LIF) | 90.6% | 1.79M | Basic LIF baseline |
 
 ## Reproduce
 
@@ -52,16 +64,29 @@ Spiking Neural Network for spoken digit classification on SHD. Achieves 91.0% wi
 git clone https://github.com/catalyst-neuromorphic/catalyst-benchmarks.git
 cd catalyst-benchmarks
 pip install -e .
+
+# N3 (91.0%)
 python shd/train.py --neuron adlif --hidden 1536 --epochs 200 --device cuda:0 --amp
+
+# N2 (84.5%)
+python shd/train.py --neuron adlif --hidden 512 --epochs 200 --device cuda:0
+
+# N1 (90.6%)
+python shd/train.py --neuron lif --hidden 1024 --epochs 200 --device cuda:0
+```
+
+## Deploy to Catalyst Hardware
+
+```bash
+python shd/deploy.py --checkpoint shd_model.pt --threshold-hw 1000
 ```
 
 ## Links
 
 - **Benchmark repo**: [catalyst-neuromorphic/catalyst-benchmarks](https://github.com/catalyst-neuromorphic/catalyst-benchmarks)
-- **Cloud API**: [catalyst-neuromorphic.com](https://catalyst-neuromorphic.com)
+- **Hardware**: [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