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I have a multi-label dataset with 727253 labeled images. Smallest label occurence is ~15 and largest around 200000. Model training started ~18h ago and failed now with the following message:

Unable to deploy model

cancel_lro() got an unexpected keyword argument 'min_nodes'

Pipeline d884756f14314048b7a036f5b07f0fd2 timeout.

The automatically generated email contained the following:

Last error message

Please reference 116298312436989152 when reporting errors.

Is this already known? Also I chose the free plan (1h) to train. Do I need to increase this to work properly? Is there any way to see a status during training to predict large waiting times without outcome? (I tried the API but there was no percentage or anything like else, only for finished models.)

Thanks in advance!

Philipp
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1 Answers1

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This seems like an internal error. The main problem seems to be that the pipeline timed out. As part of the timeout it tries to do some sort of cleanup and this cleanup seems to have a bug.

My recommendation is re-try the pipeline.

Michal K
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