except I want it to be the EPOCH_COMPLETED(every=50) of the training epoch, not the evaluator epoch…

It means that you would like to save a model (not the best one) every 50-th epoch completed. This is easy following the doc of ModelCheckpoint
handler = ModelCheckpoint(“models/”, “checkpoint”, n_saved=None)

trainer.add_event_handler(EPOCH_COMPLETED(every=50), handler)

so, here is a complete working example
!rm -rf /tmp/models

import os
from ignite.engine import Engine, Events
from ignite.handlers import ModelCheckpoint
from torch import nn
trainer = Engine(lambda engine, batch: None)
handler = ModelCheckpoint('/tmp/models', 'myprefix', n_saved=None, create_dir=True)
model = nn.Linear(3, 3)
trainer.add_event_handler(Events.EPOCH_COMPLETED(every=50), handler, {'mymodel': model})
trainer.run([0], max_epochs=200)

!ls /tmp/models

HTH
PS. there was a typo in the docstring which i’ve just fixed