So far, @cjnani16 has only been able to train on 1% of the data due to hardware constraints. One advantage of moving to Nyla is that training on the entire dataset (potentially many times over) should be do-able.
Implementation
[ ] Verify that running training script using 1% of data works as expected on Nyla, i.e., run the exact same notebook that has been running on Amoxicillin to make sure the packages are all installed as expected.
[ ] Write a notebook that trains using the entire dataset and run on Nyla. Save checkpoints to disk (and copy to Amoxicillin if desired).
[ ] Work with @eshedmargalit to convert that notebook into a robust/reproducible python script that can be executed in isolation.
Following up on Issue #3 :
Motivation
So far, @cjnani16 has only been able to train on 1% of the data due to hardware constraints. One advantage of moving to Nyla is that training on the entire dataset (potentially many times over) should be do-able.
Implementation