data_name=nq_knowledge_boundary

export CUDA_VISIBLE_DEVICES=0,1,2,3
export DATA_DIR=data/${data_name} # first download the data from https://huggingface.co/datasets/PeterJinGo/nq_hotpotqa_train

# export BASE_MODEL="/mnt/hzy/searchr1_verl_checkpoints/2025-03-23-15:05:05-nq-kb-search-r1-grpo-qwen2.5-3b-it-em/actor/global_step_500"
export BASE_MODEL="/mnt/hzy/searchr1_verl_checkpoints/2025-03-23-14:52:20-nq-vanilla-search-r1-grpo-qwen2.5-3b-it-em/actor/global_step_300"
# export BASE_MODEL="PeterJinGo/SearchR1-nq_hotpotqa_train-qwen2.5-3b-em-grpo"
# set -x
export VLLM_ATTENTION_BACKEND=XFORMERS # vllm + qwen2-7b with flash_attn has some issues

# max_prompt_length = (config['training']['max_start_length'] + config['training']['max_response_length'] * (config['training']['max_turns'] - 1) + config['training']['max_obs_length'] * config['training']['max_turns'])

PYTHONUNBUFFERED=1 python3 -m verl.trainer.main_ppo \
    data.train_files=$DATA_DIR/train.parquet \
    data.val_files=$DATA_DIR/test.parquet \
    data.train_data_num=null \
    data.val_data_num=null \
    data.train_batch_size=512 \
    data.val_batch_size=1024 \
    data.max_prompt_length=4096 \
    data.max_response_length=500 \
    data.max_start_length=2048 \
    data.max_obs_length=500 \
    data.shuffle_train_dataloader=True \
    algorithm.adv_estimator=gae \
    actor_rollout_ref.model.path=$BASE_MODEL \
    actor_rollout_ref.actor.optim.lr=1e-6 \
    actor_rollout_ref.model.enable_gradient_checkpointing=true \
    actor_rollout_ref.model.use_remove_padding=True \
    actor_rollout_ref.actor.optim.lr_warmup_steps_ratio=0.95 \
    actor_rollout_ref.actor.ppo_mini_batch_size=256 \
    actor_rollout_ref.actor.ppo_micro_batch_size=64 \
    actor_rollout_ref.actor.fsdp_config.param_offload=true \
    actor_rollout_ref.actor.fsdp_config.grad_offload=true \
    actor_rollout_ref.actor.fsdp_config.optimizer_offload=true \
    actor_rollout_ref.rollout.log_prob_micro_batch_size=128 \
    actor_rollout_ref.rollout.tensor_model_parallel_size=1 \
    actor_rollout_ref.rollout.name=vllm \
    actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
    actor_rollout_ref.ref.log_prob_micro_batch_size=128 \
    actor_rollout_ref.ref.fsdp_config.param_offload=True \
    actor_rollout_ref.rollout.n_agent=1 \
    actor_rollout_ref.rollout.temperature=0 \
    actor_rollout_ref.actor.state_masking=true \
    critic.optim.lr=1e-5 \
    critic.model.use_remove_padding=True \
    critic.optim.lr_warmup_steps_ratio=0.05 \
    critic.model.path=$BASE_MODEL \
    critic.model.enable_gradient_checkpointing=true \
    critic.ppo_micro_batch_size=8 \
    critic.model.fsdp_config.param_offload=true \
    critic.model.fsdp_config.grad_offload=true \
    critic.model.fsdp_config.optimizer_offload=true \
    algorithm.kl_ctrl.kl_coef=0.001 \
    algorithm.no_think_rl=false \
    trainer.critic_warmup=0 \
    trainer.logger=[] \
    +trainer.val_only=true \
    +trainer.val_before_train=true \
    trainer.default_hdfs_dir=null \
    trainer.n_gpus_per_node=4 \
    trainer.nnodes=1 \
    max_turns=4 \
    retriever.url="http://127.0.0.1:8000/retrieve" \
    retriever.topk=3
