Add many missing spaces in adjacent strings (#26751)

Add missing spaces in adjacent strings

examples/flax/image-captioning/run_image_captioning_flax.py

@@ -203,7 +203,7 @@ class ModelArguments:
         metadata={
             "help": (
                 "Whether or not to allow for custom models defined on the Hub in their own modeling files. This option"
-                "should only be set to `True` for repositories you trust and in which you have read the code, as it will"
+                "should only be set to `True` for repositories you trust and in which you have read the code, as it will "
                 "execute code present on the Hub on your local machine."
             )
         },
@@ -256,7 +256,7 @@ class DataTrainingArguments:
         metadata={
             "help": (
                 "The maximum total sequence length for validation target text after tokenization. Sequences longer "
-                "than this will be truncated, sequences shorter will be padded. Will default to `max_target_length`."
+                "than this will be truncated, sequences shorter will be padded. Will default to `max_target_length`. "
                 "This argument is also used to override the `max_length` param of `model.generate`, which is used "
                 "during evaluation."
             )
@@ -423,7 +423,7 @@ def main():
         and not training_args.overwrite_output_dir
     ):
         raise ValueError(
-            f"Output directory ({training_args.output_dir}) already exists and is not empty."
+            f"Output directory ({training_args.output_dir}) already exists and is not empty. "
             "Use --overwrite_output_dir to overcome."
         )
 
@@ -685,7 +685,7 @@ def main():
     eval_batch_size = int(training_args.per_device_eval_batch_size) * jax.device_count()
     if training_args.block_size % train_batch_size > 0 or training_args.block_size % eval_batch_size > 0:
         raise ValueError(
-            "`training_args.block_size` needs to be a multiple of the global train/eval batch size."
+            "`training_args.block_size` needs to be a multiple of the global train/eval batch size. "
             f"Got {training_args.block_size}, {train_batch_size} and {eval_batch_size} respectively instead."
         )