diff --git a/pointwise_cnn_harmonic_matched/README.md b/pointwise_cnn_harmonic_matched/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d7a6d7da404801807cd546a2a110e163edfd4015 --- /dev/null +++ b/pointwise_cnn_harmonic_matched/README.md @@ -0,0 +1,18 @@ +# Tsinghua SSVEP — Equivalent CNN (pointwise_cnn, harmonic_matched) + +Auto-generated model card. Trained by `train_baseline_cnn.py`. + +## Architecture & Configuration +- **Model Architecture**: `pointwise_cnn` (Pointwise / Temporal 1D CNN) +- **Spike Encoder**: `harmonic_matched` +- **Input Channels**: `2880` +- **Classes**: `41` +- **Total Parameters**: `1,617,746` (Exact 1:1 Match with SNN SpikingMLP) +- **Hidden Layers**: `512,256` +- **Dropout**: `0.3` +- **T Timesteps / Bins**: `100` + +## Validation Accuracy +- **Best Accuracy**: **`97.11%`** +- **Epochs Completed**: `150` / `150` +- **Learning Rate**: `0.002` with Cosine Annealing diff --git a/pointwise_cnn_harmonic_matched/best/metrics.json b/pointwise_cnn_harmonic_matched/best/metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..244c8552c77d95c0db5ea414c383e02d8d2e0ce7 --- /dev/null +++ b/pointwise_cnn_harmonic_matched/best/metrics.json @@ -0,0 +1,10 @@ +{ + "epoch": 132, + "train_loss": 0.3812156021595001, + "train_acc": 1.0, + "val_acc": 0.9710714285714286, + "val_tgt_acc": 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