Add model card creation snippet to example scripts (#13730)

* Update run_glue.py

* Update run_glue.py

* Add model creation snippet to other scripts

* Fix style

examples/pytorch/language-modeling/run_clm.py

@@ -500,7 +500,6 @@ def main():
         trainer.log_metrics("eval", metrics)
         trainer.save_metrics("eval", metrics)
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "text-generation"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -510,7 +509,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/language-modeling/run_mlm.py

@@ -528,7 +528,6 @@ def main():
         trainer.log_metrics("eval", metrics)
         trainer.save_metrics("eval", metrics)
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "fill-mask"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -538,7 +537,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/language-modeling/run_plm.py

@@ -499,7 +499,6 @@ def main():
         trainer.log_metrics("eval", metrics)
         trainer.save_metrics("eval", metrics)
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "language-modeling"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -509,7 +508,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/multiple-choice/run_swag.py

@@ -430,8 +430,7 @@ def main():
         trainer.log_metrics("eval", metrics)
         trainer.save_metrics("eval", metrics)
 
-    if training_args.push_to_hub:
-        trainer.push_to_hub(
+    kwargs = dict(
         finetuned_from=model_args.model_name_or_path,
         tasks="multiple-choice",
         dataset_tags="swag",
@@ -440,6 +439,11 @@ def main():
         language="en",
     )
 
+    if training_args.push_to_hub:
+        trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
+
 
 def _mp_fn(index):
     # For xla_spawn (TPUs)

examples/pytorch/question-answering/run_qa.py

@@ -623,7 +623,6 @@ def main():
         trainer.log_metrics("predict", metrics)
         trainer.save_metrics("predict", metrics)
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "question-answering"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -633,7 +632,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/question-answering/run_qa_beam_search.py

@@ -656,7 +656,6 @@ def main():
         trainer.log_metrics("predict", metrics)
         trainer.save_metrics("predict", metrics)
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "question-answering"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -666,7 +665,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/summarization/run_summarization.py

@@ -622,7 +622,6 @@ def main():
                 with open(output_prediction_file, "w") as writer:
                     writer.write("\n".join(predictions))
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "summarization"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -632,7 +631,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
     return results
 

examples/pytorch/text-classification/run_glue.py

@@ -546,7 +546,6 @@ def main():
                             item = label_list[item]
                             writer.write(f"{index}\t{item}\n")
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "text-classification"}
     if data_args.task_name is not None:
         kwargs["language"] = "en"
@@ -554,7 +553,10 @@ def main():
         kwargs["dataset_args"] = data_args.task_name
         kwargs["dataset"] = f"GLUE {data_args.task_name.upper()}"
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/token-classification/run_ner.py

@@ -542,7 +542,6 @@ def main():
                 for prediction in true_predictions:
                     writer.write(" ".join(prediction) + "\n")
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "token-classification"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -552,7 +551,10 @@ def main():
         else:
             kwargs["dataset"] = data_args.dataset_name
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

examples/pytorch/translation/run_translation.py

@@ -590,7 +590,6 @@ def main():
                 with open(output_prediction_file, "w", encoding="utf-8") as writer:
                     writer.write("\n".join(predictions))
 
-    if training_args.push_to_hub:
     kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "translation"}
     if data_args.dataset_name is not None:
         kwargs["dataset_tags"] = data_args.dataset_name
@@ -604,7 +603,10 @@ def main():
     if len(languages) > 0:
         kwargs["language"] = languages
 
+    if training_args.push_to_hub:
         trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
 
     return results