| set -x |
|
|
| export CUDA_DEVICE_MAX_CONNECTIONS=1 |
|
|
| gsm8k_train_path=$HOME/data/gsm8k/train.parquet |
| gsm8k_test_path=$HOME/data/gsm8k/test.parquet |
| math_train_path=$HOME/data/math/train.parquet |
| math_test_path=$HOME/data/math/test.parquet |
|
|
| train_files="['$gsm8k_train_path', '$math_train_path']" |
| test_files="['$gsm8k_test_path', '$math_test_path']" |
|
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| python3 -m verl.trainer.main_ppo --config-path=./config --config-name='ppo_megatron_trainer'\ |
| algorithm.adv_estimator=gae \ |
| data.train_files="$train_files" \ |
| data.val_files="$test_files" \ |
| data.train_batch_size=1024 \ |
| data.max_prompt_length=1024 \ |
| data.max_response_length=512 \ |
| data.filter_overlong_prompts=True \ |
| data.truncation='error' \ |
| actor_rollout_ref.model.path=Qwen/Qwen2-7B-Instruct \ |
| 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=4 \ |
| actor_rollout_ref.actor.megatron.pipeline_model_parallel_size=2 \ |
| actor_rollout_ref.actor.megatron.tensor_model_parallel_size=2 \ |
| actor_rollout_ref.actor.use_kl_loss=False \ |
| 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=0.4 \ |
| actor_rollout_ref.ref.megatron.pipeline_model_parallel_size=2 \ |
| actor_rollout_ref.ref.megatron.tensor_model_parallel_size=2 \ |
| critic.optim.lr=1e-5 \ |
| critic.model.path=Qwen/Qwen2-7B-Instruct \ |
| critic.ppo_micro_batch_size_per_gpu=4 \ |
| algorithm.use_kl_in_reward=False \ |
| trainer.critic_warmup=0 \ |
| trainer.logger='["console","wandb"]' \ |
| trainer.project_name='verl_ppo_gsm8k_math_examples' \ |
| trainer.experiment_name='qwen2_7b_megatron' \ |
| trainer.n_gpus_per_node=8 \ |
| trainer.nnodes=1 \ |
| trainer.save_freq=20 \ |
| trainer.test_freq=5 \ |
| trainer.total_epochs=100 $@ |
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