taborzbislaw

The problem exists even if I run training for smaller number of epochs (e.g. 400) and then start training from a saved checkpoint. From training logs it appears that learning...

It appears that I have found the source of the problem: one MUST NOT change the maximal number of epochs when resuming training because the learning rate does depend not...

Hi, changing dataset and continuing training on the modified dataset is a separate problem. If you do that you must rerun nnUNet_plan and proprocess on the new dataset and then...

Hi, yes, you can, but to continue training with increased number of epochs and changed dataset you must modify nnUNet scripts (at least nnUNetTrainerV2.py) and pickle files splits_final.pkl and (likely)...

Hi, sorry for my mistake, concerning learning rate scheduler and thank you for the explanations. Best Zbisław

Or at least how to apply transform between moving and fixed image to some other image e.g. mask

When I start elasticsearch using sudo docker run -p 9200:9200 -e "discovery.type=single-node" -e "ES_JAVA_OPTS=-Xms1024m -Xmx1024m" -e "xpack.security.enabled=false" docker.elastic.co/elasticsearch/elasticsearch:8.13.2 examples from https://docs.haystack.deepset.ai/docs/elasticsearchbm25retriever work correctly But when docker is started with security...

Hi, thank you very much for your prompt answer. I am using custom models in evaluations and it works very well. Just one more question. When optimizing prompts I prepare...

Hi, can you, please, give some working example of optimization using structured output? There is no complete code in opik webpage so I was trying to compose thr code from...

Thank you for the hint "invoke_llm() function should return a string". Now optimization works