Quick fix for pipeline tasks to get learning rate correct

tasks/finetune_utils.py

@@ -129,10 +129,14 @@ def _build_train_valid_dataloaders(train_dataset, valid_dataset):
                                           args.num_workers, not args.keep_last)
     valid_dataloader = _build_infinite_size_dataloader(valid_dataloader_)
 
-    # Now that we've built the data loaders, set args.micro_batch_size to
-    # the actual batch size the model will see for this dataset
+    # Now that we've built the data loaders, set batch_size arguments
+    # to the actual batch size the model will see for this dataset.
+    # This is necessary so pipeline transfers know what size they are
+    # and the LR schedule, which is based on samples seen, gets set
+    # correctly.
     if hasattr(train_dataset, 'sample_multiplier'):
         args.micro_batch_size *= train_dataset.sample_multiplier
+        args.global_batch_size *= train_dataset.sample_multiplier
 
     return train_dataloader, valid_dataloader