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How To Version Models While Training In Production

how to version models
while training in production

Posted one month ago
Votes Newest

Answers 6

This sounds like you don't have clearml installed in the ubuntu container. Either this, or your clearml.conf in the container is not pointing to the server, as a result all information is missing.

I'd rather suggest you change the approach, and run a clearml-agent setup with docker and when you want to run YOLOv5 training you actually execute it remotely on the queue that the agent is listening to

Posted one month ago

I have configured it perfectly
Iam able to send data from the container to clearml server

If clearml-agent is the only way
Can you provide any documentation

Posted one month ago

Hi @<1639074542859063296:profile|StunningSwallow12> , here are the docs for the agent - None

Posted one month ago


Posted one month ago

I have run the Ubuntu 20.04 container and cloned YOLOv5 inside it. Within the container, I configured ClearML (self-hosting server) with access keys and credentials.

I am launching YOLOv5 training with project and name tags. However, experiment results are not being logged to the ClearML server; instead, they are saved inside the container's root directory under the <project/name> folder.

Interestingly, when I tried running the process directly on the host machine, the experiment results were successfully logged to the ClearML server. It's worth noting that I am able to send data from the container to the ClearML server, but the training results are not being logged.

Posted one month ago

Hey @<1639074542859063296:profile|StunningSwallow12> what exactly do you mean by "training in production"? Maybe you can elaborate what kind of models too.

ClearML in general assigns a unique Model ID to each model, but if you need some other way of versioning, we have support for custom tags, and you can apply those programmatically on the model

Posted one month ago
6 Answers
one month ago
one month ago
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