Borui Wei / Tom and Kick Public
Target: Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz) Clone this project
Experiments EON Tuner
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

No name set

Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz)

100 ms

256 kB

1024 kB

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General

F1-score

Precision

Recall

100%
mfe-conv1d-feb
PERFORMANCE
LATENCY
127 ms of 100 ms
Exceeds target by 27 ms
RAM
17 kB of 256 kB
ROM
38 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 100%

Type Filters Kernel Rate
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

3/21/2023, 11:53:27 PM

92%
mfcc-conv1d-0da
PERFORMANCE
LATENCY
206 ms of 100 ms
Exceeds target by 106 ms
RAM
24 kB of 256 kB
ROM
165 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 92%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
conv1d 256 3 -
dropout - - 0.25

3/21/2023, 11:51:16 PM

92%
spectr-conv1d-cad
PERFORMANCE
LATENCY
55 ms of 100 ms
RAM
20 kB of 256 kB
ROM
66 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 92%

Type Filters Kernel Rate
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.25

3/21/2023, 11:51:38 PM

88%
mfcc-conv1d-724
PERFORMANCE
LATENCY
261 ms of 100 ms
Exceeds target by 161 ms
RAM
18 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.032 | 0.032 | 40

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 88%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

3/21/2023, 11:55:04 PM

88%
mfe-conv1d-422
PERFORMANCE
LATENCY
116 ms of 100 ms
Exceeds target by 16 ms
RAM
18 kB of 256 kB
ROM
65 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 88%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.25

3/21/2023, 11:58:41 PM

85%
mfcc-conv1d-bae
PERFORMANCE
LATENCY
201 ms of 100 ms
Exceeds target by 101 ms
RAM
17 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 85%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

3/21/2023, 11:49:10 PM

85%
mfcc-conv1d-05c
PERFORMANCE
LATENCY
242 ms of 100 ms
Exceeds target by 142 ms
RAM
25 kB of 256 kB
ROM
165 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 40

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 85%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
conv1d 256 3 -
dropout - - 0.5

3/21/2023, 11:53:05 PM

81%
spectr-conv1d-d1a
PERFORMANCE
LATENCY
177 ms of 100 ms
Exceeds target by 77 ms
RAM
41 kB of 256 kB
ROM
39 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.025 | 0.0125 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 81%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

3/21/2023, 11:51:06 PM

81%
spectr-conv1d-63b
PERFORMANCE
LATENCY
55 ms of 100 ms
RAM
20 kB of 256 kB
ROM
66 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -52

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 81%

Type Filters Kernel Rate
Data augmentation
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.5

3/21/2023, 11:54:39 PM

81%
mfe-conv1d-84a
PERFORMANCE
LATENCY
17 ms of 100 ms
RAM
7 kB of 256 kB
ROM
38 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 81%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

3/21/2023, 11:58:02 PM

81%
mfcc-conv1d-fb8
PERFORMANCE
LATENCY
260 ms of 100 ms
Exceeds target by 160 ms
RAM
18 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.032 | 0.032 | 40

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 81%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

3/21/2023, 11:59:35 PM

77%
mfcc-conv2d-8ef
PERFORMANCE
LATENCY
208 ms of 100 ms
Exceeds target by 108 ms
RAM
19 kB of 256 kB
ROM
52 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 40

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 77%

Type Filters Kernel Rate
Data augmentation
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
conv2d 64 3 -
dropout - - 0.25

3/21/2023, 11:48:47 PM

77%
spectr-conv2d-50f
PERFORMANCE
LATENCY
121 ms of 100 ms
Exceeds target by 21 ms
RAM
22 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 77%

Type Filters Kernel Rate
Data augmentation
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
dropout - - 0.5

3/21/2023, 11:55:01 PM

77%
mfe-conv2d-a76
PERFORMANCE
LATENCY
129 ms of 100 ms
Exceeds target by 29 ms
RAM
19 kB of 256 kB
ROM
33 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 77%

Type Filters Kernel Rate
Data augmentation
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
dropout - - 0.5

3/21/2023, 11:54:40 PM

77%
mfe-conv1d-b04
PERFORMANCE
LATENCY
116 ms of 100 ms
Exceeds target by 16 ms
RAM
18 kB of 256 kB
ROM
65 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 77%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.5

3/21/2023, 11:55:08 PM

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