update optimizer run_squad

run_squad_pytorch.py

@@ -800,13 +800,17 @@ def main():
     if n_gpu > 1:
         model = torch.nn.DataParallel(model)
 
-    optimizer = BERTAdam([{'params': [p for n, p in model.named_parameters() if n != 'bias'], 'l2': 0.01},
-                          {'params': [p for n, p in model.named_parameters() if n == 'bias'], 'l2': 0.}
-                         ],
-                         lr=args.learning_rate, schedule='warmup_linear',
+    no_decay = ['bias', 'gamma', 'beta']
+    optimizer_parameters = [
+        {'params': [p for n, p in model.named_parameters() if n not in no_decay], 'weight_decay_rate': 0.01},
+        {'params': [p for n, p in model.named_parameters() if n in no_decay], 'weight_decay_rate': 0.0}
+        ]
+
+    optimizer = BERTAdam(optimizer_parameters,
+                         lr=args.learning_rate,
                          warmup=args.warmup_proportion,
                          t_total=num_train_steps)
-    
+
     global_step = 0
     if args.do_train:
         train_features = convert_examples_to_features(