Fix ROUGE add example check and update README (#18398)

* Fix ROUGE add example check and update README

* Stay consistent in values

examples/pytorch/summarization/run_summarization.py

@@ -625,12 +625,9 @@ def main():
         decoded_preds, decoded_labels = postprocess_text(decoded_preds, decoded_labels)
 
         result = metric.compute(predictions=decoded_preds, references=decoded_labels, use_stemmer=True)
-        # Extract a few results from ROUGE
-        result = {key: value.mid.fmeasure * 100 for key, value in result.items()}
-
+        result = {k: round(v * 100, 4) for k, v in result.items()}
         prediction_lens = [np.count_nonzero(pred != tokenizer.pad_token_id) for pred in preds]
         result["gen_len"] = np.mean(prediction_lens)
-        result = {k: round(v, 4) for k, v in result.items()}
         return result
 
     # Initialize our Trainer

examples/pytorch/summarization/run_summarization_no_trainer.py

@@ -51,10 +51,13 @@ from transformers import (
     SchedulerType,
     get_scheduler,
 )
-from transformers.utils import get_full_repo_name, is_offline_mode, send_example_telemetry
+from transformers.utils import check_min_version, get_full_repo_name, is_offline_mode, send_example_telemetry
 from transformers.utils.versions import require_version
 
 
+# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
+check_min_version("4.22.0.dev0")
+
 logger = get_logger(__name__)
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")
 
@@ -707,10 +710,7 @@ def main():
                     references=decoded_labels,
                 )
         result = metric.compute(use_stemmer=True)
-        # Extract a few results from ROUGE
-        result = {key: value.mid.fmeasure * 100 for key, value in result.items()}
-
-        result = {k: round(v, 4) for k, v in result.items()}
+        result = {k: round(v * 100, 4) for k, v in result.items()}
 
         logger.info(result)