[Examples] Add automatic dataset splitting in language-modeling examples (#9133)

* replaced jnp.split + removing textual model inputs + ensuring warmup_steps > 0

* Add automatic dataset splitting in language-modeling examples

examples/language-modeling/run_plm.py

@@ -93,6 +93,12 @@ class DataTrainingArguments:
     overwrite_cache: bool = field(
         default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
     )
+    validation_split_percentage: Optional[int] = field(
+        default=5,
+        metadata={
+            "help": "The percentage of the train set used as validation set in case there's no validation split"
+        },
+    )
     max_seq_length: int = field(
         default=512,
         metadata={
@@ -196,6 +202,17 @@ def main():
     if data_args.dataset_name is not None:
         # Downloading and loading a dataset from the hub.
         datasets = load_dataset(data_args.dataset_name, data_args.dataset_config_name)
+        if "validation" not in datasets.keys():
+            datasets["validation"] = load_dataset(
+                data_args.dataset_name,
+                data_args.dataset_config_name,
+                split=f"train[:{data_args.validation_split_percentage}%]",
+            )
+            datasets["train"] = load_dataset(
+                data_args.dataset_name,
+                data_args.dataset_config_name,
+                split=f"train[{data_args.validation_split_percentage}%:]",
+            )
     else:
         data_files = {}
         if data_args.train_file is not None: