refactor adapter hparam

Former-commit-id: f82aece9ebd6df83a7a005cc7cbbcec07fa6e14d

README_zh.md

@@ -274,8 +274,8 @@ CUDA_VISIBLE_DEVICES=0 USE_MODELSCOPE_HUB=1 python src/train_web.py
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
     --stage pt \
-    --model_name_or_path path_to_llama_model \
     --do_train \
+    --model_name_or_path path_to_llama_model \
     --dataset wiki_demo \
     --finetuning_type lora \
     --lora_target q_proj,v_proj \
@@ -297,8 +297,8 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
     --stage sft \
-    --model_name_or_path path_to_llama_model \
     --do_train \
+    --model_name_or_path path_to_llama_model \
     --dataset alpaca_gpt4_zh \
     --template default \
     --finetuning_type lora \
@@ -321,14 +321,14 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
     --stage rm \
-    --model_name_or_path path_to_llama_model \
     --do_train \
+    --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_sft_checkpoint \
+    --create_new_adapter \
     --dataset comparison_gpt4_zh \
     --template default \
     --finetuning_type lora \
     --lora_target q_proj,v_proj \
-    --resume_lora_training False \
-    --checkpoint_dir path_to_sft_checkpoint \
     --output_dir path_to_rm_checkpoint \
     --per_device_train_batch_size 2 \
     --gradient_accumulation_steps 4 \
@@ -346,14 +346,14 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
     --stage ppo \
-    --model_name_or_path path_to_llama_model \
     --do_train \
+    --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_sft_checkpoint \
+    --create_new_adapter \
     --dataset alpaca_gpt4_zh \
     --template default \
     --finetuning_type lora \
     --lora_target q_proj,v_proj \
-    --resume_lora_training False \
-    --checkpoint_dir path_to_sft_checkpoint \
     --reward_model path_to_rm_checkpoint \
     --output_dir path_to_ppo_checkpoint \
     --per_device_train_batch_size 2 \
@@ -377,14 +377,14 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
     --stage dpo \
-    --model_name_or_path path_to_llama_model \
     --do_train \
+    --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_sft_checkpoint \
+    --create_new_adapter \
     --dataset comparison_gpt4_zh \
     --template default \
     --finetuning_type lora \
     --lora_target q_proj,v_proj \
-    --resume_lora_training False \
-    --checkpoint_dir path_to_sft_checkpoint \
     --output_dir path_to_dpo_checkpoint \
     --per_device_train_batch_size 2 \
     --gradient_accumulation_steps 4 \
@@ -472,9 +472,9 @@ deepspeed --num_gpus 8 --master_port=9901 src/train_bash.py \
 ```bash
 python src/export_model.py \
     --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_checkpoint \
     --template default \
     --finetuning_type lora \
-    --checkpoint_dir path_to_checkpoint \
     --export_dir path_to_export
 ```
 
@@ -486,9 +486,9 @@ python src/export_model.py \
 ```bash
 python src/api_demo.py \
     --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_checkpoint \
     --template default \
-    --finetuning_type lora \
-    --checkpoint_dir path_to_checkpoint
+    --finetuning_type lora
 ```
 
 > [!TIP]
@@ -499,9 +499,9 @@ python src/api_demo.py \
 ```bash
 python src/cli_demo.py \
     --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_checkpoint \
     --template default \
-    --finetuning_type lora \
-    --checkpoint_dir path_to_checkpoint
+    --finetuning_type lora
 ```
 
 ### 浏览器测试
@@ -509,9 +509,9 @@ python src/cli_demo.py \
 ```bash
 python src/web_demo.py \
     --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_checkpoint \
     --template default \
-    --finetuning_type lora \
-    --checkpoint_dir path_to_checkpoint
+    --finetuning_type lora
 ```
 
 ### 模型评估
@@ -519,9 +519,9 @@ python src/web_demo.py \
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/evaluate.py \
     --model_name_or_path path_to_llama_model \
-    --finetuning_type lora \
-    --checkpoint_dir path_to_checkpoint \
+    --adapter_name_or_path path_to_checkpoint \
     --template vanilla \
+    --finetuning_type lora \
     --task ceval \
     --split validation \
     --lang zh \
@@ -534,12 +534,12 @@ CUDA_VISIBLE_DEVICES=0 python src/evaluate.py \
 ```bash
 CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
     --stage sft \
-    --model_name_or_path path_to_llama_model \
     --do_predict \
+    --model_name_or_path path_to_llama_model \
+    --adapter_name_or_path path_to_checkpoint \
     --dataset alpaca_gpt4_zh \
     --template default \
     --finetuning_type lora \
-    --checkpoint_dir path_to_checkpoint \
     --output_dir path_to_predict_result \
     --per_device_eval_batch_size 8 \
     --max_samples 100 \