finetuning any BERT model - fixes #455

examples/lm_finetuning/finetune_on_pregenerated.py

@@ -123,9 +123,8 @@ def main():
     parser = ArgumentParser()
     parser.add_argument('--pregenerated_data', type=Path, required=True)
     parser.add_argument('--output_dir', type=Path, required=True)
-    parser.add_argument("--bert_model", type=str, required=True,
-                        choices=["bert-base-uncased", "bert-large-uncased", "bert-base-cased",
-                                 "bert-base-multilingual", "bert-base-chinese"])
+    parser.add_argument("--bert_model", type=str, required=True, help="Bert pre-trained model selected in the list: bert-base-uncased, "
+                             "bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.")
     parser.add_argument("--do_lower_case", action="store_true")
     parser.add_argument("--reduce_memory", action="store_true",
                         help="Store training data as on-disc memmaps to massively reduce memory usage")