diff --git a/bitbrain/finetune/run.sh b/bitbrain/finetune/run.sh
index bae7524..eff94ad 100644
--- a/bitbrain/finetune/run.sh
+++ b/bitbrain/finetune/run.sh
@@ -1,53 +1,50 @@
-##########################
 # llama factory start script
 ##########################
-#CUDA_VISIBLE_DEVICES=5,6 python ../LLaMA-Factory/src/train.py \
-export LLaMA_PATH=/home/chenyuhang/LLaMA-Factory
+export LLaMA_PATH="llama_factory本地路径"
 OUTPUT_DIR="输出路径"
-#export CUDA_DEVICE_ORDER=PCI_BUS_ID
-export CUDA_VISIBLE_DEVICES=4,5,6,7 
+export CUDA_VISIBLE_DEVICES=0,1,2,3
 export NCCL_P2P_LEVEL=NVL
 export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
 
-# 可设置混合策略：     --mix_strategy interleave_over\
-#    --interleave_probs 0.1,0.35,0.2,0.2,0.1,0.05 \
-
-# 可设置自定义的评估数据集  --eval_dataset ceval,cmmlu \
 
-
-FORCE_TORCHRUN=1 CUDA_VISIBLE_DEVICES=4,5,6,7  torchrun --nproc_per_node 4 $LLaMA_PATH/src/train.py \
+FORCE_TORCHRUN=1 CUDA_VISIBLE_DEVICES=0,1,2,3   torchrun --nproc_per_node 4 $LLaMA_PATH/src/train.py \
     --stage sft \
     --do_train \
-    --model_name_or_path "预训练模型路径" \
+    --model_name_or_path "模型路径" \
     --cutoff_len 2048 \
     --dataset_dir "数据集路径" \
-    --dataset shared_gpt_format\
+    --dataset chinese_instruct,deepctrl_200k,ultrachat_200k,code_feedback_custom \
     --overwrite_cache \
-    --max_samples 5000000 \
-    --packing True \
+    --enable_liger_kernel True\
+    --packing False \
     --use_swanlab true \
     --report_to swanlab \
-    --run_name sft_bit-brain \
+    --swanlab_project "swanlab项目名称" \
+    --run_name "运行名称" \
     --preprocessing_num_workers 30 \
     --template qwen \
     --finetuning_type full \
-    --output_dir ${OUTPUT_DIR}/sft \
+    --output_dir ${OUTPUT_DIR}/"本次运行保存子路径" \
     --overwrite_output_dir \
-    --per_device_train_batch_size 16 \
+    --per_device_train_batch_size 4 \
     --per_device_eval_batch_size 4 \
     --do_eval \
     --val_size 100 \
     --eval_strategy steps \
     --eval_steps 1000 \
-    --flash_attn sdpa\
-    --gradient_accumulation_steps 4 \
+    --flash_attn fa2\
+    --gradient_accumulation_steps 16 \
     --lr_scheduler_type cosine \
+    --warmup_ratio 0.0125 \
+    --max_grad_norm 1.0 \
     --logging_steps 10 \
-    --save_steps 500 \
-    --learning_rate 3e-4 \
+    --save_steps 5000 \
+    --learning_rate 2e-5 \
     --weight_decay 0.01 \
-    --num_train_epochs 4.0 \
+    --num_train_epochs 3.0 \
     --plot_loss \
-    --bf16 \
-    --resume_from_checkpoint "恢复训练的checkpoint路径"
+    --bf16 
+    
+    #--resume_from_checkpoint ${OUTPUT_DIR}/"本次运行保存子路径/checkpoint-xxxx"
+