[run_clm] clarify why we get the tokenizer warning on long input (#11145)

* clarify why we get the warning here

* Update examples/language-modeling/run_clm.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* wording

* style

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

examples/language-modeling/run_clm.py

@@ -43,6 +43,7 @@ from transformers import (
     default_data_collator,
     set_seed,
 )
+from transformers.testing_utils import CaptureLogger
 from transformers.trainer_utils import get_last_checkpoint, is_main_process
 from transformers.utils import check_min_version
 
@@ -317,7 +318,15 @@ def main():
     text_column_name = "text" if "text" in column_names else column_names[0]
 
     def tokenize_function(examples):
-        return tokenizer(examples[text_column_name])
+        tok_logger = transformers.utils.logging.get_logger("transformers.tokenization_utils_base")
+        with CaptureLogger(tok_logger) as cl:
+            output = tokenizer(examples[text_column_name])
+        # clm input could be much much longer than block_size
+        if "Token indices sequence length is longer than the" in cl.out:
+            tok_logger.warning(
+                "^^^^^^^^^^^^^^^^ Please ignore the warning above - this long input will be chunked into smaller bits before being passed to the model."
+            )
+        return output
 
     tokenized_datasets = datasets.map(
         tokenize_function,