Slow NER training with GPU - SpaCy v3.2

I am using GPU to train a NER model from Scratch in SpaCy v3.2 (with the --gpu-id option) and SLURM job scheduler:

sbatch -p gpu --gres = gpu: v100: 1 my_script.sh

Here is the "my_script.sh" submission script:

#! / bin / bash

python -m spacy train config.cfg --output ./output --paths.train ./train.spacy --paths.dev ./train.spacy --gpu-id 0

When I use nvidia-smi, I can clearly see GPU usage at 7% with memory usage at 0% (slow). That's why, I think that adjustments on my side are to be made at the level of the SpaCy to optimize its use.

Could you please tell me where this slow training with GPU comes from?

Thanks in advance,

Slow NER training with GPU - SpaCy v3.2

0 Answers