set -x HF_MODEL_PATH=Qwen/Qwen3-30B-A3B DIST_CKPT_PATH=${DIST_CKPT_PATH} python scripts/converter_hf_to_mcore.py --hf_model_path $HF_MODEL_PATH --output_path $DIST_CKPT_PATH export CUDA_DEVICE_MAX_CONNECTIONS=1 # For megatron communication/computation overlapping python3 -m verl.trainer.main_ppo --config-path=config \ --config-name='ppo_megatron_trainer.yaml'\ algorithm.adv_estimator=grpo \ data.train_files=$HOME/data/gsm8k/train.parquet \ data.val_files=$HOME/data/gsm8k/test.parquet \ data.train_batch_size=64 \ data.max_prompt_length=1024 \ data.max_response_length=2048 \ data.filter_overlong_prompts=True \ data.truncation='error' \ actor_rollout_ref.model.path=$HF_MODEL_PATH \ actor_rollout_ref.actor.optim.lr=1e-6 \ actor_rollout_ref.actor.ppo_mini_batch_size=64 \ actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=4 \ actor_rollout_ref.actor.megatron.pipeline_model_parallel_size=2 \ actor_rollout_ref.actor.megatron.tensor_model_parallel_size=4 \ actor_rollout_ref.actor.megatron.expert_model_parallel_size=4 \ actor_rollout_ref.actor.megatron.use_dist_checkpointing=True \ actor_rollout_ref.actor.megatron.dist_checkpointing_path=$DIST_CKPT_PATH \ actor_rollout_ref.actor.use_kl_loss=True \ actor_rollout_ref.actor.kl_loss_coef=0.001 \ actor_rollout_ref.actor.kl_loss_type=low_var_kl \ actor_rollout_ref.actor.entropy_coeff=0 \ actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=4 \ actor_rollout_ref.rollout.tensor_model_parallel_size=4 \ actor_rollout_ref.rollout.name=vllm \ actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \ actor_rollout_ref.rollout.n=5 \ actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=4 \ actor_rollout_ref.ref.megatron.pipeline_model_parallel_size=2 \ actor_rollout_ref.ref.megatron.tensor_model_parallel_size=4 \ actor_rollout_ref.ref.megatron.expert_model_parallel_size=4 \ actor_rollout_ref.ref.megatron.use_dist_checkpointing=True \ actor_rollout_ref.ref.megatron.dist_checkpointing_path=$DIST_CKPT_PATH \ algorithm.use_kl_in_reward=False \ trainer.critic_warmup=0 \ trainer.logger='["console","wandb"]' \ trainer.project_name='verl_grpo_example_gsm8k_math' \ trainer.experiment_name='qwen3_30b_moe_megatron' \ trainer.n_gpus_per_node=8 \ trainer.nnodes=4 \ trainer.save_freq=20 \ trainer.test_freq=5 \ trainer.total_epochs=15 $@