Finalize lm examples (#8188)

* Finish the cleanup of the language-modeling examples

* Update main README

* Apply suggestions from code review

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Apply suggestions from code review

Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Propagate changes

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

examples/language-modeling/run_plm.py

@@ -96,7 +96,7 @@ class DataTrainingArguments:
         default=None,
         metadata={
             "help": "The maximum total input sequence length after tokenization. Sequences longer "
-            "than this will be truncated."
+            "than this will be truncated. Default to the max input length of the model."
         },
     )
     preprocessing_num_workers: Optional[int] = field(
@@ -172,10 +172,10 @@ def main():
 
     # Get the datasets: you can either provide your own CSV/JSON/TXT training and evaluation files (see below)
     # or just provide the name of one of the public datasets available on the hub at https://huggingface.co/datasets/
-    # (the dataset will be downloaded automatically from the datasets Hub
+    # (the dataset will be downloaded automatically from the datasets Hub).
     #
-    # For CSV/JSON files, this script will use the column called 'text' or the first column. You can easily tweak this
-    # behavior (see below)
+    # For CSV/JSON files, this script will use the column called 'text' or the first column if no column called
+    # 'text' is found. You can easily tweak this behavior (see below).
     #
     # In distributed training, the load_dataset function guarantee that only one local process can concurrently
     # download the dataset.