Dwi Ahmad Dzulhijjah / DBlindForDiscriminativeAI 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

Run #6

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

100 ms

256 kB

1024 kB

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General

F1-score

Precision

Recall

77%
mfe-conv2d-b5c
PERFORMANCE
LATENCY
36 ms of 100 ms
RAM
10 kB of 256 kB
ROM
38 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 77%

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

1/5/2025, 11:02:40 AM

70%
mfe-conv1d-274
PERFORMANCE
LATENCY
7 ms of 100 ms
RAM
5 kB of 256 kB
ROM
42 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 70%

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

1/5/2025, 11:03:54 AM

68%
mfe-conv1d-9db
PERFORMANCE
LATENCY
10 ms of 100 ms
RAM
9 kB of 256 kB
ROM
70 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 68%

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

1/5/2025, 11:02:54 AM

66%
mfcc-conv1d-251
PERFORMANCE
LATENCY
9 ms of 100 ms
RAM
8 kB of 256 kB
ROM
69 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFCC

0.05 | 0.05 | 40

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 66%

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

1/5/2025, 11:07:46 AM

65%
mfe-conv1d-604
PERFORMANCE
LATENCY
28 ms of 100 ms
RAM
9 kB of 256 kB
ROM
71 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 65%

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

1/5/2025, 11:05:28 AM

65%
mfcc-conv1d-f63
PERFORMANCE
LATENCY
9 ms of 100 ms
RAM
8 kB of 256 kB
ROM
69 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFCC

0.05 | 0.05 | 40

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 65%

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

1/5/2025, 11:05:40 AM

64%
mfcc-conv2d-9bf
PERFORMANCE
LATENCY
23 ms of 100 ms
RAM
8 kB of 256 kB
ROM
57 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 64%

Type Filters Kernel Rate
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
conv2d 64 3 -
dropout - - 0.5

1/5/2025, 11:04:35 AM

61%
mfe-conv1d-0d0
PERFORMANCE
LATENCY
23 ms of 100 ms
RAM
8 kB of 256 kB
ROM
70 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 61%

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

1/5/2025, 11:05:06 AM

58%
mfcc-conv1d-2a6
PERFORMANCE
LATENCY
5 ms of 100 ms
RAM
5 kB of 256 kB
ROM
40 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 40

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 58%

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

1/5/2025, 11:05:48 AM

55%
mfcc-conv1d-c66
PERFORMANCE
LATENCY
23 ms of 100 ms
RAM
8 kB of 256 kB
ROM
68 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

MFCC

0.032 | 0.032 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 55%

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

1/5/2025, 11:02:50 AM

50%
mfcc-conv1d-048
PERFORMANCE
LATENCY
3 ms of 100 ms
RAM
5 kB of 256 kB
ROM
42 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 50%

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

1/5/2025, 11:05:42 AM

49%
mfe-conv1d-001
PERFORMANCE
LATENCY
7 ms of 100 ms
RAM
8 kB of 256 kB
ROM
70 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 49%

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

1/5/2025, 11:04:28 AM

18%
spectr-conv1d-f61
PERFORMANCE
LATENCY
13 ms of 100 ms
RAM
9 kB of 256 kB
ROM
47 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

SPECTROGRAM

0.025 | 0.025 | -52

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 18%

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

1/5/2025, 11:07:16 AM

10%
spectr-conv1d-91e
PERFORMANCE
LATENCY
9 ms of 100 ms
RAM
12 kB of 256 kB
ROM
72 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

SPECTROGRAM

0.025 | 0.025 | -72

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 10%

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

1/5/2025, 11:04:24 AM

0%
spectr-conv1d-1f2
PERFORMANCE
LATENCY
15 ms of 100 ms
RAM
15 kB of 256 kB
ROM
46 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

SPECTROGRAM

0.025 | 0.0125 | -52

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 0%

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

1/5/2025, 11:06:08 AM

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