diff --git a/src/llmtuner/hparams/finetuning_args.py b/src/llmtuner/hparams/finetuning_args.py
index 43e5e9e0..69403cc2 100644
--- a/src/llmtuner/hparams/finetuning_args.py
+++ b/src/llmtuner/hparams/finetuning_args.py
@@ -17,6 +17,7 @@ class FreezeArguments:
                   BLOOM & Falcon & ChatGLM choices: ["mlp", "self_attention"], \
                   Qwen choices: ["mlp", "attn"], \
                   Phi choices: ["mlp", "mixer"], \
+                  InternLM2 choices: ["feed_forward", "attention"], \
                   Others choices: the same as LLaMA.'
         },
     )
diff --git a/src/llmtuner/model/adapter.py b/src/llmtuner/model/adapter.py
index c4a1a3b9..3d3f95c0 100644
--- a/src/llmtuner/model/adapter.py
+++ b/src/llmtuner/model/adapter.py
@@ -52,8 +52,18 @@ def init_adapter(
         else:  # fine-tuning the first n layers if num_layer_trainable < 0
             trainable_layer_ids = [k for k in range(-finetuning_args.num_layer_trainable)]  # noqa: C416
 
+        freeze_modules = set()
+        for name, _ in model.named_modules():
+            if "0." in name:
+                freeze_modules.add(name.split("0.")[-1].split(".")[0])
+
         trainable_layers = []
         for module_name in finetuning_args.name_module_trainable:
+            if module_name not in freeze_modules:
+                raise ValueError(
+                    "Module {} is not found, please choose from {}".format(module_name, ", ".join(freeze_modules))
+                )
+
             for idx in trainable_layer_ids:
                 trainable_layers.append("{:d}.{}".format(idx, module_name))