Tobias Lindhorst / Alerto2 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 #4

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

100 ms

256 kB

1024 kB

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General

F1-score

Precision

Recall

Run #5 (Mar 25 2025, 13:02:33, finished) Run #4 (Mar 25 2025, 12:40:42, failed) Run #3 (Mar 25 2025, 12:06:07, failed) Run #2 (Mar 25 2025, 11:59:56, failed) Run #1 (Mar 25 2025, 11:49:34, failed)
88%
mfe-conv1d-7c9
View
PERFORMANCE
LATENCY
4 ms of 100 ms
RAM
5 kB of 256 kB
ROM
32 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
500 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 88%

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

3/25/2025, 12:50:14 PM

87%
mfe-conv1d-fc3
PERFORMANCE
LATENCY
245 ms of 100 ms
Exceeds target by 145 ms
RAM
25 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 87%

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

3/25/2025, 12:45:55 PM

83%
mfe-conv1d-989
PERFORMANCE
LATENCY
244 ms of 100 ms
Exceeds target by 144 ms
RAM
25 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
500 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 83%

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

3/25/2025, 12:52:06 PM

82%
mfe-conv1d-c79
PERFORMANCE
LATENCY
132 ms of 100 ms
Exceeds target by 32 ms
RAM
20 kB of 256 kB
ROM
70 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
2000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 82%

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

3/25/2025, 12:44:27 PM

81%
spectr-conv2d-4f9
PERFORMANCE
LATENCY
150 ms of 100 ms
Exceeds target by 50 ms
RAM
31 kB of 256 kB
ROM
39 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
500 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -72

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 81%

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

3/25/2025, 12:52:49 PM

80%
mfe-conv1d-585
PERFORMANCE
LATENCY
125 ms of 100 ms
Exceeds target by 25 ms
RAM
16 kB of 256 kB
ROM
35 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
2000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 80%

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

3/25/2025, 12:49:53 PM

79%
mfcc-conv1d-eae
PERFORMANCE
LATENCY
235 ms of 100 ms
Exceeds target by 135 ms
RAM
23 kB of 256 kB
ROM
69 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
500 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 79%

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

3/25/2025, 12:46:43 PM

78%
mfe-conv1d-8c6
PERFORMANCE
LATENCY
7 ms of 100 ms
RAM
9 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 78%

Type Filters Kernel Rate
Data augmentation
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.25

3/25/2025, 12:50:47 PM

77%
mfe-conv1d-989
PERFORMANCE
LATENCY
127 ms of 100 ms
Exceeds target by 27 ms
RAM
17 kB of 256 kB
ROM
35 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 77%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.25

3/25/2025, 12:44:52 PM

72%
mfcc-conv1d-f42
PERFORMANCE
LATENCY
222 ms of 100 ms
Exceeds target by 122 ms
RAM
18 kB of 256 kB
ROM
32 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 72%

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

3/25/2025, 12:51:42 PM

72%
mfe-conv1d-7db
PERFORMANCE
LATENCY
5 ms of 100 ms
RAM
6 kB of 256 kB
ROM
35 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
2000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 72%

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

3/25/2025, 12:44:21 PM

69%
mfcc-conv1d-812
PERFORMANCE
LATENCY
3 ms of 100 ms
RAM
4 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
2000 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 69%

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

3/25/2025, 12:49:59 PM

69%
mfe-conv1d-5e9
PERFORMANCE
LATENCY
131 ms of 100 ms
Exceeds target by 31 ms
RAM
20 kB of 256 kB
ROM
70 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 69%

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

3/25/2025, 12:48:07 PM

69%
mfe-conv1d-5de
PERFORMANCE
LATENCY
245 ms of 100 ms
Exceeds target by 145 ms
RAM
25 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
500 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 69%

Type Filters Kernel Rate
Data augmentation
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.25

3/25/2025, 12:51:35 PM

66%
mfe-conv1d-65b
PERFORMANCE
LATENCY
124 ms of 100 ms
Exceeds target by 24 ms
RAM
16 kB of 256 kB
ROM
35 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

2000 ms |
500 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (OVERALL)
CLASSIFICATION

0.005 | 100 | 66%

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

3/25/2025, 12:47:44 PM

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