RAGEN / example_bash.sh
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set -e
USE_GRPO="algorithm.adv_estimator=grpo"
USE_PPO="algorithm.adv_estimator=gae"
USE_BASE="algorithm.kl_ctrl.kl_coef=0.0 actor_rollout_ref.actor.kl_loss_coef=0.0 actor_rollout_ref.actor.clip_ratio_high=0.28 actor_rollout_ref.rollout.rollout_filter_ratio=0.25"
python train.py --config-name _3_frozen_lake \
system.CUDA_VISIBLE_DEVICES="'0,1,2,3,4,5,6,7'" \
trainer.project_name=ragen_latest_qwen2.5_3B_it_explict \
trainer.n_gpus_per_node=8 \
model_path= \
trainer.save_freq=200 \
trainer.experiment_name=frozenlake_slippery $USE_PPO $USE_BASE