|
|
| export PYTORCH_CUDA_ALLOC_CONF="" |
| export EXPERIMENT_NAME=llm_guard_3B_10k_v2 |
| export WAND_PROJECT='guard' |
| export CUDA_DEVICE_ORDER="PCI_BUS_ID" |
| export CUDA_VISIBLE_DEVICES=1,2 |
| export VLLM_ATTENTION_BACKEND=FLASH_ATTN |
|
|
|
|
| PYTHONUNBUFFERED=1 NCCL_P2P_DISABLE=1 NCCL_IB_DISABLE=1 python3 -m verl.trainer.main_ppo \ |
| data.train_files=/home/mshahidul/readctrl/code/RL_model/verl/Search-R1/dataset/train.parquet \ |
| data.val_files=/home/mshahidul/readctrl/code/RL_model/verl/Search-R1/dataset/test.parquet \ |
| data.train_batch_size=64 \ |
| data.val_batch_size=64 \ |
| data.max_prompt_length=4096 \ |
| data.max_response_length=1024 \ |
| data.shuffle_train_dataloader=True \ |
| algorithm.adv_estimator=grpo \ |
| actor_rollout_ref.model.path=Qwen/Qwen3-4B-Instruct-2507 \ |
| actor_rollout_ref.model.enable_gradient_checkpointing=true \ |
| actor_rollout_ref.model.use_remove_padding=False \ |
| 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=16 \ |
| actor_rollout_ref.actor.fsdp_config.param_offload=true \ |
| actor_rollout_ref.actor.fsdp_config.optimizer_offload=true \ |
| actor_rollout_ref.rollout.log_prob_micro_batch_size=64 \ |
| actor_rollout_ref.rollout.tensor_model_parallel_size=1 \ |
| actor_rollout_ref.rollout.name=vllm \ |
| actor_rollout_ref.rollout.gpu_memory_utilization=0.4 \ |
| actor_rollout_ref.ref.log_prob_micro_batch_size=64 \ |
| actor_rollout_ref.ref.fsdp_config.param_offload=True \ |
| actor_rollout_ref.actor.kl_loss_coef=0.001 \ |
| trainer.logger=['wandb'] \ |
| trainer.n_gpus_per_node=2 \ |
| trainer.nnodes=1 \ |
| trainer.save_freq=100 \ |
| trainer.test_freq=50 \ |
| trainer.project_name=$WANDB_PROJECT \ |
| trainer.experiment_name=$EXPERIMENT_NAME \ |
| trainer.total_epochs=15 \ |
| trainer.total_training_steps=1005 \ |
| trainer.default_local_dir=verl_checkpoints/$EXPERIMENT_NAME \ |
| do_search=false \ |
| max_turns=1 \ |
| 2>&1 | tee $EXPERIMENT_NAME.log |
