tensorflow / tensorflow/models
Question on the mobileNetV2 convergence time.
@marksandler2 is already working on this.
Since Feb 9, 2021.
- Dominant language
- Python
- Stars
- 77.7k
- Forks
- 44.8k
- PR merge metrics
- No merged PRs in 30d
Description
I found this information in https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/README.md The numbers above can be reproduced using slim's train_image_classifier. Below is the set of parameters that achieves 72.0% for full size MobileNetV2, after about 700K when trained on 8 GPU. If trained on a single GPU the full convergence is after 5.5M steps. Also note that learning rate and num_epochs_per_decay both need to be adjusted depending on how many GPUs are being used due to slim's internal averaging.
I wonder what is run time to achieve this convergence?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.