updating examples and doc

examples/lm_finetuning/finetune_on_pregenerated.py

@@ -16,7 +16,7 @@ from tqdm import tqdm
 from pytorch_transformers import WEIGHTS_NAME, CONFIG_NAME
 from pytorch_transformers.modeling_bert import BertForPreTraining
 from pytorch_transformers.tokenization_bert import BertTokenizer
-from pytorch_transformers.optimization import BertAdam, WarmupLinearSchedule
+from pytorch_transformers.optimization import AdamW, WarmupLinearSchedule
 
 InputFeatures = namedtuple("InputFeatures", "input_ids input_mask segment_ids lm_label_ids is_next")
 
@@ -273,7 +273,7 @@ def main():
         warmup_linear = WarmupLinearSchedule(warmup=args.warmup_proportion,
                                              t_total=num_train_optimization_steps)
     else:
-        optimizer = BertAdam(optimizer_grouped_parameters,
+        optimizer = AdamW(optimizer_grouped_parameters,
                              lr=args.learning_rate,
                              warmup=args.warmup_proportion,
                              t_total=num_train_optimization_steps)