Skip to content

Log the right train_batch_size if using auto_find_batch_size and also log the adjusted value seperately. #23800

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 3 commits into from
May 26, 2023
Merged

Log the right train_batch_size if using auto_find_batch_size and also log the adjusted value seperately. #23800

Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
88e00a6
Log right bs
muellerzr May 26, 2023
848afc9
Log
muellerzr May 26, 2023
70f17fa
Diff message
muellerzr May 26, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 2 additions & 1 deletion src/transformers/trainer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1704,6 +1704,7 @@ def _inner_training_loop(
self, batch_size=None, args=None, resume_from_checkpoint=None, trial=None, ignore_keys_for_eval=None
):
self._train_batch_size = batch_size
logger.debug(f"Currently training with a batch size of: {self._train_batch_size}")
# Data loader and number of training steps
train_dataloader = self.get_train_dataloader()

Expand Down Expand Up @@ -1811,7 +1812,7 @@ def _inner_training_loop(
logger.info("***** Running training *****")
logger.info(f" Num examples = {num_examples:,}")
logger.info(f" Num Epochs = {num_train_epochs:,}")
logger.info(f" Instantaneous batch size per device = {args.per_device_train_batch_size:,}")
logger.info(f" Instantaneous batch size per device = {self._train_batch_size:,}")
logger.info(f" Total train batch size (w. parallel, distributed & accumulation) = {total_train_batch_size:,}")
logger.info(f" Gradient Accumulation steps = {args.gradient_accumulation_steps}")
logger.info(f" Total optimization steps = {max_steps:,}")
Expand Down