fix PPO trainer #551 , update readme

Former-commit-id: faead74849470cebae9e37cde5fab2a71b32aa43

src/llmtuner/hparams/finetuning_args.py

@@ -8,7 +8,7 @@ class FinetuningArguments:
     r"""
     Arguments pertaining to which techniques we are going to fine-tuning with.
     """
-    finetuning_type: Optional[Literal["none", "freeze", "lora", "full"]] = field(
+    finetuning_type: Optional[Literal["lora", "freeze", "full", "none"]] = field(
         default="lora",
         metadata={"help": "Which fine-tuning method to use."}
     )
@@ -49,7 +49,7 @@ class FinetuningArguments:
         metadata={"help": "Dropout rate for the LoRA fine-tuning."}
     )
     lora_target: Optional[str] = field(
-        default="q_proj,v_proj",
+        default=None,
         metadata={"help": "Name(s) of target modules to apply LoRA. Use commas to separate multiple modules. \
                   LLaMA choices: [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\"], \
                   BLOOM & Falcon choices: [\"query_key_value\", \"self_attention.dense\", \"mlp.dense\"], \
@@ -77,7 +77,7 @@ class FinetuningArguments:
 
         self.trainable_layers = ["{:d}.{}".format(idx, self.name_module_trainable) for idx in trainable_layer_ids]
 
-        assert self.finetuning_type in ["none", "freeze", "lora", "full"], "Invalid fine-tuning method."
+        assert self.finetuning_type in ["lora", "freeze", "full", "none"], "Invalid fine-tuning method."
 
     def save_to_json(self, json_path: str):
         r"""Saves the content of this instance in JSON format inside `json_path`."""