set -x
export VLLM_ATTENTION_BACKEND=XFORMERS

export BASE_MODEL={{Qwen2.5-7B-Instruct-R1 Path}}
export DATA_DIR=experiments/data
export EXPERIMENT_NAME=DianJin-R1-7B
export REWARD_PATH=reward_score_cflue.py
export REWARD_NAME=compute_score
export SAVE_DIR=experiments/checkpoints/$EXPERIMENT_NAME

nohup python3 -m verl.trainer.main_ppo \
    algorithm.adv_estimator=grpo \
    data.train_files=$DATA_DIR/train.parquet \
    data.val_files=$DATA_DIR/val.parquet \
    data.train_batch_size=1024 \
    data.max_prompt_length=1024 \
    data.max_response_length=4096 \
    data.filter_overlong_prompts=True \
    data.truncation='error' \
    actor_rollout_ref.model.path=$BASE_MODEL \
    actor_rollout_ref.model.enable_gradient_checkpointing=True \
    actor_rollout_ref.model.use_remove_padding=True \
    actor_rollout_ref.actor.optim.lr=1e-6 \
    actor_rollout_ref.actor.ppo_mini_batch_size=256 \
    actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=8 \
    actor_rollout_ref.actor.use_kl_loss=True \
    actor_rollout_ref.actor.kl_loss_coef=0.001 \
    actor_rollout_ref.actor.kl_loss_type=low_var_kl \
    actor_rollout_ref.actor.entropy_coeff=0 \
    actor_rollout_ref.actor.fsdp_config.param_offload=True \
    actor_rollout_ref.actor.fsdp_config.optimizer_offload=True \
    actor_rollout_ref.actor.checkpoint.contents=['model','hf_model','optimizer','extra'] \
    actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=8 \
    actor_rollout_ref.rollout.tensor_model_parallel_size=4 \
    actor_rollout_ref.rollout.name=vllm \
    actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
    actor_rollout_ref.rollout.temperature=0.6 \
    actor_rollout_ref.rollout.top_p=0.95 \
    actor_rollout_ref.rollout.n=8 \
    actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=8 \
    actor_rollout_ref.ref.fsdp_config.param_offload=True \
    algorithm.kl_ctrl.kl_coef=0.001 \
    custom_reward_function.path=$REWARD_PATH \
    custom_reward_function.name=$REWARD_NAME \
    trainer.critic_warmup=0 \
    trainer.logger=['console'] \
    trainer.project_name=$EXPERIMENT_NAME \
    trainer.experiment_name=$EXPERIMENT_NAME \
    trainer.n_gpus_per_node=8 \
    trainer.nnodes=1 \
    trainer.save_freq=50 \
    trainer.test_freq=10 \
    trainer.default_local_dir=$SAVE_DIR \
    trainer.total_epochs=15 >experiments/logs/$EXPERIMENT_NAME.log 2>&1 &