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set -x
ENGINE=${1:-vllm}
export VLLM_ATTENTION_BACKEND=XFORMERS
python3 -m verl.trainer.main_ppo \
algorithm.adv_estimator=grpo \
data.train_files=$HOME/data/geo3k/train.parquet \
data.val_files=$HOME/data/geo3k/test.parquet \
data.train_batch_size=512 \
data.max_prompt_length=1024 \
data.max_response_length=2048 \
data.filter_overlong_prompts=True \
data.truncation='error' \
data.image_key=images \
actor_rollout_ref.model.path=Qwen/Qwen2.5-VL-7B-Instruct \
actor_rollout_ref.actor.optim.lr=1e-6 \
actor_rollout_ref.model.use_remove_padding=True \
actor_rollout_ref.actor.ppo_mini_batch_size=128 \
actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=10 \
actor_rollout_ref.actor.use_kl_loss=True \
actor_rollout_ref.actor.kl_loss_coef=0.01 \
actor_rollout_ref.actor.kl_loss_type=low_var_kl \
actor_rollout_ref.actor.entropy_coeff=0 \
actor_rollout_ref.model.enable_gradient_checkpointing=True \
actor_rollout_ref.actor.fsdp_config.param_offload=False \
actor_rollout_ref.actor.fsdp_config.optimizer_offload=False \
actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=20 \
actor_rollout_ref.rollout.tensor_model_parallel_size=2 \
actor_rollout_ref.rollout.name=$ENGINE \
actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
actor_rollout_ref.rollout.enable_chunked_prefill=False \
actor_rollout_ref.rollout.enforce_eager=False \
actor_rollout_ref.rollout.free_cache_engine=False \
actor_rollout_ref.rollout.n=5 \
actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=20 \
actor_rollout_ref.ref.fsdp_config.param_offload=True \
algorithm.use_kl_in_reward=False \
trainer.critic_warmup=0 \
trainer.logger=['console','wandb'] \
trainer.project_name='verl_grpo_example_geo3k' \
trainer.experiment_name='qwen2_5_vl_7b_function_rm' \
trainer.n_gpus_per_node=8 \
trainer.nnodes=1 \
trainer.save_freq=-1 \
trainer.test_freq=5 \
trainer.total_epochs=15 $@ |