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  1. pointwise_cnn_harmonic_matched/README.md +0 -18
  2. pointwise_cnn_harmonic_matched/best/metrics.json +0 -10
  3. pointwise_cnn_harmonic_matched/best/model.pt +0 -3
  4. pointwise_cnn_harmonic_matched/best/optimizer.pt +0 -3
  5. pointwise_cnn_harmonic_matched/best_model.pt +0 -3
  6. pointwise_cnn_harmonic_matched/checkpoints/best.json +0 -4
  7. pointwise_cnn_harmonic_matched/checkpoints/epoch_0132/metrics.json +0 -10
  8. pointwise_cnn_harmonic_matched/checkpoints/epoch_0132/model.pt +0 -3
  9. pointwise_cnn_harmonic_matched/checkpoints/epoch_0132/optimizer.pt +0 -3
  10. pointwise_cnn_harmonic_matched/checkpoints/epoch_0148/metrics.json +0 -10
  11. pointwise_cnn_harmonic_matched/checkpoints/epoch_0148/model.pt +0 -3
  12. pointwise_cnn_harmonic_matched/checkpoints/epoch_0148/optimizer.pt +0 -3
  13. pointwise_cnn_harmonic_matched/checkpoints/epoch_0149/metrics.json +0 -10
  14. pointwise_cnn_harmonic_matched/checkpoints/epoch_0149/model.pt +0 -3
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  16. pointwise_cnn_harmonic_matched/checkpoints/epoch_0150/metrics.json +0 -10
  17. pointwise_cnn_harmonic_matched/checkpoints/epoch_0150/model.pt +0 -3
  18. pointwise_cnn_harmonic_matched/checkpoints/epoch_0150/optimizer.pt +0 -3
  19. pointwise_cnn_harmonic_matched/checkpoints/latest.json +0 -1
  20. pointwise_cnn_harmonic_matched/final_summary.json +0 -10
  21. pointwise_cnn_harmonic_matched/last/metrics.json +0 -10
  22. pointwise_cnn_harmonic_matched/last/model.pt +0 -3
  23. pointwise_cnn_harmonic_matched/last/optimizer.pt +0 -3
  24. pointwise_cnn_harmonic_matched/last_model.pt +0 -3
  25. pointwise_cnn_harmonic_matched/metrics/epoch_0001.json +0 -10
  26. pointwise_cnn_harmonic_matched/metrics/epoch_0002.json +0 -10
  27. pointwise_cnn_harmonic_matched/metrics/epoch_0003.json +0 -10
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  30. pointwise_cnn_harmonic_matched/metrics/epoch_0006.json +0 -10
  31. pointwise_cnn_harmonic_matched/metrics/epoch_0007.json +0 -10
  32. pointwise_cnn_harmonic_matched/metrics/epoch_0008.json +0 -10
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pointwise_cnn_harmonic_matched/README.md DELETED
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- # Tsinghua SSVEP — Equivalent CNN (pointwise_cnn, harmonic_matched)
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-
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- Auto-generated model card. Trained by `train_baseline_cnn.py`.
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-
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- ## Architecture & Configuration
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- - **Model Architecture**: `pointwise_cnn` (Pointwise / Temporal 1D CNN)
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- - **Spike Encoder**: `harmonic_matched`
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- - **Input Channels**: `2880`
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- - **Classes**: `41`
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- - **Total Parameters**: `1,617,746` (Exact 1:1 Match with SNN SpikingMLP)
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- - **Hidden Layers**: `512,256`
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- - **Dropout**: `0.3`
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- - **T Timesteps / Bins**: `100`
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-
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- ## Validation Accuracy
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- - **Best Accuracy**: **`97.11%`**
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- - **Epochs Completed**: `150` / `150`
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- - **Learning Rate**: `0.002` with Cosine Annealing
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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