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EON Tuner

The EON Tuner helps you find the most optimal architecture for your embedded machine-learning application. Clone this project to use the EON Tuner.

Target

No name set

Continuous audio

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

100 ms

256 kB

1024 kB

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F1-score

Precision

Recall

100%
mfe-conv1d-428
Show logs
PERFORMANCE
LATENCY
416 ms of 100 ms
Exceeds target by 316 ms
RAM
30 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
INPUT

4000 ms | 1000 ms

MFE

0.05 | 0.05 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 2:47:44 AM

99%
mfe-conv1d-de4
Show logs
PERFORMANCE
LATENCY
265 ms of 100 ms
Exceeds target by 165 ms
RAM
26 kB of 256 kB
ROM
68 kB of 1024 kB
DSP NN Unused
INPUT

2000 ms | 1000 ms

MFE

0.05 | 0.05 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:11:26 AM

99%
spectr-conv1d-12c
Show logs
PERFORMANCE
LATENCY
71 ms of 100 ms
RAM
27 kB of 256 kB
ROM
70 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 500 ms

SPECTROGRAM

0.025 | 0.025 | -72

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 2:52:55 AM

99%
spectr-conv1d-196
Show logs
PERFORMANCE
LATENCY
161 ms of 100 ms
Exceeds target by 61 ms
RAM
38 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 500 ms

SPECTROGRAM

0.025 | 0.0125 | -72

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:12:23 AM

99%
spectr-conv1d-548
Show logs
PERFORMANCE
LATENCY
203 ms of 100 ms
Exceeds target by 103 ms
RAM
40 kB of 256 kB
ROM
43 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 1000 ms

SPECTROGRAM

0.025 | 0.0125 | -52

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 2:59:33 AM

98%
mfe-conv1d-165
Show logs
PERFORMANCE
LATENCY
183 ms of 100 ms
Exceeds target by 83 ms
RAM
25 kB of 256 kB
ROM
68 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 1000 ms

MFE

0.05 | 0.025 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:09:04 AM

98%
spectr-conv2d-c34
Show logs
PERFORMANCE
LATENCY
2082 ms of 100 ms
Exceeds target by 1982 ms
RAM
31 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 500 ms

SPECTROGRAM

0.075 | 0.0375 | -52

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:01:13 AM

98%
spectr-conv1d-8c9
Show logs
PERFORMANCE
LATENCY
302 ms of 100 ms
Exceeds target by 202 ms
RAM
41 kB of 256 kB
ROM
42 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 250 ms

SPECTROGRAM

0.025 | 0.0125 | -52

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:06:58 AM

97%
spectr-conv1d-ebf
Show logs
PERFORMANCE
LATENCY
212 ms of 100 ms
Exceeds target by 112 ms
RAM
38 kB of 256 kB
ROM
36 kB of 1024 kB
DSP NN Unused
INPUT

2000 ms | 500 ms

SPECTROGRAM

0.025 | 0.025 | -72

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:14:32 AM

97%
mfe-conv1d-207
Show logs
PERFORMANCE
LATENCY
139 ms of 100 ms
Exceeds target by 39 ms
RAM
19 kB of 256 kB
ROM
41 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 250 ms

MFE

0.032 | 0.032 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 2:55:53 AM

97%
mfe-conv1d-a80
Show logs
PERFORMANCE
LATENCY
353 ms of 100 ms
Exceeds target by 253 ms
RAM
30 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
INPUT

2000 ms | 1000 ms

MFE

0.05 | 0.025 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:08:12 AM

96%
spectr-conv1d-bc7
Show logs
PERFORMANCE
LATENCY
194 ms of 100 ms
Exceeds target by 94 ms
RAM
41 kB of 256 kB
ROM
42 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 500 ms

SPECTROGRAM

0.025 | 0.0125 | -52

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:04:41 AM

96%
spectr-conv1d-283
Show logs
PERFORMANCE
LATENCY
138 ms of 100 ms
Exceeds target by 38 ms
RAM
20 kB of 256 kB
ROM
69 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 1000 ms

SPECTROGRAM

0.075 | 0.075 | -72

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:01:58 AM

95%
mfe-conv1d-1e0
Show logs
PERFORMANCE
LATENCY
229 ms of 100 ms
Exceeds target by 129 ms
RAM
26 kB of 256 kB
ROM
68 kB of 1024 kB
DSP NN Unused
INPUT

2000 ms | 500 ms

MFE

0.05 | 0.05 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 2:52:40 AM

95%
mfe-conv1d-a59
Show logs
PERFORMANCE
LATENCY
266 ms of 100 ms
Exceeds target by 166 ms
RAM
26 kB of 256 kB
ROM
68 kB of 1024 kB
DSP NN Unused
INPUT

1000 ms | 1000 ms

MFE

0.05 | 0.025 | 32

ACCURACY
CLASSIFICATION (KERAS)

0.005 | 100

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

10/27/2022, 3:09:21 AM

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