The EON Tuner helps you quickly run hyper-parameter sweeps that explore different pre-processing + model architectures optimized for your defined objectives. Clone this project to use the EON Tuner.
Target
Run #2
ECO
500 ms
200000 kB
200000 kB
Filters
Status
DSP type
Model type
View
Data set
Variant
Sort
General
F1-score
Precision
Recall
Run #2 (Nov 21 2025, 19:00:10, finished)
spectr-35f
PERFORMANCE
LATENCY
500 ms
RAM
200000 kB
ROM
200000 kB
Unused
TIME-SERIES INPUT
5000 ms
|
500 ms
|
Enabled
SPECTROGRAM
| Parameter | Value |
|---|---|
| id | 38 |
| show_axes | true |
| dspBlockId | 78 |
| fft_length | 128 |
| frame_length | 0.05 |
| frame_stride | 0.05 |
| noise_floor_db | -52 |
| implementationVersion | 4 |
KERAS
| Parameter | Value |
|---|---|
| id | 39 |
| dsp | 38 |
| layers | [object Object],[object Object],[object Object],[object Object],[object Object],[object Object] |
| batchSize | 32 |
| learningRate | 0.005 |
| trainTestSplit | 0.2 |
| trainingCycles | 100 |
| minimumConfidenceRating | 0.6 |
ANOMALY-GMM
| Parameter | Value |
|---|---|
| id | 75 |
| axes | audio RMS,audio Spectral Skewness,audio Spectral Kurtosis,audio Spectral Power 15.62 - 21.88 Hz,audio Spectral Power 21.88 - 28.12 Hz,audio Spectral Power 40.62 - 46.88 Hz,audio Spectral Power 171.88 - 178.12 Hz |
| clusterCount | 4 |
| minimumConfidenceRating | 14.82 |
0
Training output
Hide
Click 'Run EON Tuner' to begin
