diff --git a/outputs/2026-06-01/23-08-51/.hydra/config.yaml b/outputs/2026-06-01/23-08-51/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..bf5373dad6ad7b8941dab9abd4113694a84b8766
--- /dev/null
+++ b/outputs/2026-06-01/23-08-51/.hydra/config.yaml
@@ -0,0 +1,1005 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 400
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 1000
+ project_name: ragen
+ experiment_name: sudoku_3b_baseline
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 20
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 20
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: -1
+ batch_adjust_mode: copy
+ max_turn: 20
+ action_sep: '||'
+ max_actions_per_turn: 3
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - SimpleSudoku
+ n_groups:
+ - 8
+ val:
+ env_groups: 32
+ group_size: 16
+ env_configs:
+ tags:
+ - SimpleSudoku
+ n_groups:
+ - 32
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-07/23-18-01/.hydra/hydra.yaml b/outputs/2026-06-07/23-18-01/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..127fd55999084586b6a999be68a1cd1e9daba4f4
--- /dev/null
+++ b/outputs/2026-06-07/23-18-01/.hydra/hydra.yaml
@@ -0,0 +1,178 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath:
+ - pkg://verl.trainer.config
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas
+ - trainer.experiment_name=sokoban_3b_box2_withthink_sas
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas,trainer.experiment_name=sokoban_3b_box2_withthink_sas,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _2_sokoban
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: verl.trainer.config
+ schema: pkg
+ provider: hydra.searchpath in main
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-07/23-18-01
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-09/00-36-11/.hydra/hydra.yaml b/outputs/2026-06-09/00-36-11/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f564182f6e4c5275617856fc08cf527e045e11d1
--- /dev/null
+++ b/outputs/2026-06-09/00-36-11/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=1
+ - trainer.experiment_name=rubikscube1_withthink_sas
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube1_withthink_sas,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/00-36-11
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-09/02-32-07/.hydra/config.yaml b/outputs/2026-06-09/02-32-07/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..286a0f5fe115cc7ce1edcf44dcd08d0631c418e5
--- /dev/null
+++ b/outputs/2026-06-09/02-32-07/.hydra/config.yaml
@@ -0,0 +1,1003 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_sas
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format, for example: place 1 at
+ row 2 col 3 or 1,2,3
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 10
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 25
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-09/02-32-07/.hydra/hydra.yaml b/outputs/2026-06-09/02-32-07/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..400e9b8e1fc14258ac144dbd8795e479f7ae781a
--- /dev/null
+++ b/outputs/2026-06-09/02-32-07/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_sas
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_sas,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/02-32-07
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-09/02-32-07/.hydra/overrides.yaml b/outputs/2026-06-09/02-32-07/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..feb1671637361bcea9f0dab2e7cb763fd9b5ed25
--- /dev/null
+++ b/outputs/2026-06-09/02-32-07/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_sas
diff --git a/outputs/2026-06-09/02-32-07/train.log b/outputs/2026-06-09/02-32-07/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-09/05-39-33/.hydra/config.yaml b/outputs/2026-06-09/05-39-33/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f447d3a5dc08ffa9c095c2f4ba87f67430497398
--- /dev/null
+++ b/outputs/2026-06-09/05-39-33/.hydra/config.yaml
@@ -0,0 +1,1003 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube3_withthink_sas
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format, for example: place 1 at
+ row 2 col 3 or 1,2,3
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 3
+ max_steps: 10
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 25
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-09/05-39-33/train.log b/outputs/2026-06-09/05-39-33/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-09/11-20-05/train.log b/outputs/2026-06-09/11-20-05/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-09/11-58-39/train.log b/outputs/2026-06-09/11-58-39/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-09/13-00-35/.hydra/overrides.yaml b/outputs/2026-06-09/13-00-35/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9a752fd778f03f732ec7009e649b3089b7892429
--- /dev/null
+++ b/outputs/2026-06-09/13-00-35/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas
+- custom_envs.rubikscube.env_config.scramble_depth=3
+- trainer.experiment_name=rubikscube3_withthink_sas
diff --git a/outputs/2026-06-09/13-00-35/train.log b/outputs/2026-06-09/13-00-35/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-09/16-00-04/.hydra/config.yaml b/outputs/2026-06-09/16-00-04/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e4bf7279d1a8a6579678b9d1e8f25e692933a2ee
--- /dev/null
+++ b/outputs/2026-06-09/16-00-04/.hydra/config.yaml
@@ -0,0 +1,1003 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 400
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: sudoku_3b_action1_baseline
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format, for example: place 1 at
+ row 2 col 3 or 1,2,3
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: -1
+ batch_adjust_mode: copy
+ max_turn: 20
+ action_sep: '||'
+ max_actions_per_turn: 1
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - SimpleSudoku
+ n_groups:
+ - 8
+ val:
+ env_groups: 32
+ group_size: 16
+ env_configs:
+ tags:
+ - SimpleSudoku
+ n_groups:
+ - 32
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-09/16-05-29/.hydra/config.yaml b/outputs/2026-06-09/16-05-29/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..66b79b9af40d3bcef623bac307e6b49f2a9996e7
--- /dev/null
+++ b/outputs/2026-06-09/16-05-29/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 400
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: sudoku_3b_action1_abstraction
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: -1
+ batch_adjust_mode: copy
+ max_turn: 20
+ action_sep: '||'
+ max_actions_per_turn: 1
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - SimpleSudoku
+ n_groups:
+ - 8
+ val:
+ env_groups: 32
+ group_size: 16
+ env_configs:
+ tags:
+ - SimpleSudoku
+ n_groups:
+ - 32
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-09/16-05-29/.hydra/hydra.yaml b/outputs/2026-06-09/16-05-29/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5778884a90c70c184868f6720d7c6a2bd1d245a0
--- /dev/null
+++ b/outputs/2026-06-09/16-05-29/.hydra/hydra.yaml
@@ -0,0 +1,178 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath:
+ - pkg://verl.trainer.config
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - model_path=/mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+ - trainer.experiment_name=sudoku_3b_action1_abstraction
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,model_path=/mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct,trainer.experiment_name=sudoku_3b_action1_abstraction,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _8_sudoku
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: verl.trainer.config
+ schema: pkg
+ provider: hydra.searchpath in main
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/16-05-29
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-09/16-05-29/.hydra/overrides.yaml b/outputs/2026-06-09/16-05-29/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..64a0cc7301b91aa19ddd503b3cc0021a4725b6d1
--- /dev/null
+++ b/outputs/2026-06-09/16-05-29/.hydra/overrides.yaml
@@ -0,0 +1,5 @@
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- model_path=/mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+- trainer.experiment_name=sudoku_3b_action1_abstraction
diff --git a/outputs/2026-06-09/17-01-43/.hydra/config.yaml b/outputs/2026-06-09/17-01-43/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1c80cbc98866a50c23cdb06d7c10e1efc141a950
--- /dev/null
+++ b/outputs/2026-06-09/17-01-43/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 400
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: sokoban_3b_box1_withthink_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: -1
+ batch_adjust_mode: copy
+ max_turn: 20
+ action_sep: '||'
+ max_actions_per_turn: 1
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - CoordSokoban
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - CoordSokoban
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-09/17-01-43/.hydra/overrides.yaml b/outputs/2026-06-09/17-01-43/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..736504fc836b4f46ad7e2f65e2cc0385d00fd47e
--- /dev/null
+++ b/outputs/2026-06-09/17-01-43/.hydra/overrides.yaml
@@ -0,0 +1,5 @@
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sa
+- trainer.experiment_name=sokoban_3b_box1_withthink_sa
diff --git a/outputs/2026-06-09/17-01-43/train.log b/outputs/2026-06-09/17-01-43/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-09/20-37-55/.hydra/hydra.yaml b/outputs/2026-06-09/20-37-55/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..87c85ef28ab9ae91050f89321162207c195781e7
--- /dev/null
+++ b/outputs/2026-06-09/20-37-55/.hydra/hydra.yaml
@@ -0,0 +1,178 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath:
+ - pkg://verl.trainer.config
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas
+ - trainer.experiment_name=sokoban_3b_box1_withthink_sas
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas,trainer.experiment_name=sokoban_3b_box1_withthink_sas,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _2_sokoban
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: verl.trainer.config
+ schema: pkg
+ provider: hydra.searchpath in main
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/20-37-55
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-09/20-37-55/.hydra/overrides.yaml b/outputs/2026-06-09/20-37-55/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..475f11baa17afb9f83c85a2c15b48e94fc45ec0c
--- /dev/null
+++ b/outputs/2026-06-09/20-37-55/.hydra/overrides.yaml
@@ -0,0 +1,5 @@
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas
+- trainer.experiment_name=sokoban_3b_box1_withthink_sas
diff --git a/outputs/2026-06-09/20-37-55/train.log b/outputs/2026-06-09/20-37-55/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-12/14-59-00/.hydra/config.yaml b/outputs/2026-06-12/14-59-00/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a4823193790f7f21aef53985d7c3ef103275a2db
--- /dev/null
+++ b/outputs/2026-06-12/14-59-00/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 25
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-12/14-59-00/.hydra/hydra.yaml b/outputs/2026-06-12/14-59-00/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..97aaa33f2300dcde4cd4f424b3ea1cb8af4fc2f6
--- /dev/null
+++ b/outputs/2026-06-12/14-59-00/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-12/14-59-00
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-12/14-59-00/train.log b/outputs/2026-06-12/14-59-00/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-15/10-55-43/.hydra/config.yaml b/outputs/2026-06-15/10-55-43/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a4823193790f7f21aef53985d7c3ef103275a2db
--- /dev/null
+++ b/outputs/2026-06-15/10-55-43/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 25
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-15/10-55-43/.hydra/hydra.yaml b/outputs/2026-06-15/10-55-43/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6465df55706cd7e4ad265887b839e82d034eb3ca
--- /dev/null
+++ b/outputs/2026-06-15/10-55-43/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-15/10-55-43
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-15/10-55-43/.hydra/overrides.yaml b/outputs/2026-06-15/10-55-43/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6c8115d8cf840a67eaf1b773a62d2f9e70ebe7a4
--- /dev/null
+++ b/outputs/2026-06-15/10-55-43/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
diff --git a/outputs/2026-06-15/10-56-06/.hydra/config.yaml b/outputs/2026-06-15/10-56-06/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f4a70e4a7e80601767e9316c6fb8e82bdea743aa
--- /dev/null
+++ b/outputs/2026-06-15/10-56-06/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube3_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 3
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 25
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-15/10-56-06/.hydra/hydra.yaml b/outputs/2026-06-15/10-56-06/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a3577493a9a6fc91f5fc29cda7a0ded45b35b3a8
--- /dev/null
+++ b/outputs/2026-06-15/10-56-06/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=3
+ - trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=3,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-15/10-56-06
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-15/10-56-06/.hydra/overrides.yaml b/outputs/2026-06-15/10-56-06/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..87ddae1e99d1e01dcbfe36c56ff781dd2354f676
--- /dev/null
+++ b/outputs/2026-06-15/10-56-06/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=3
+- trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa
diff --git a/outputs/2026-06-15/10-56-06/train.log b/outputs/2026-06-15/10-56-06/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-15/17-29-15/.hydra/config.yaml b/outputs/2026-06-15/17-29-15/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5f64970b69e535d638744fcc500e56b9fffaed17
--- /dev/null
+++ b/outputs/2026-06-15/17-29-15/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 25
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-15/17-29-15/.hydra/hydra.yaml b/outputs/2026-06-15/17-29-15/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ca6d0bdbd02fffda86499371f672be43e455f62b
--- /dev/null
+++ b/outputs/2026-06-15/17-29-15/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-15/17-29-15
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-15/17-29-15/.hydra/overrides.yaml b/outputs/2026-06-15/17-29-15/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9b03123f9520a5c1cdb68fece1a6773355493194
--- /dev/null
+++ b/outputs/2026-06-15/17-29-15/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
diff --git a/outputs/2026-06-16/13-25-02/.hydra/hydra.yaml b/outputs/2026-06-16/13-25-02/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..136ef2f6b82990daac2625c031070065c24f871a
--- /dev/null
+++ b/outputs/2026-06-16/13-25-02/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-16/13-25-02
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-16/13-25-02/.hydra/overrides.yaml b/outputs/2026-06-16/13-25-02/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9b03123f9520a5c1cdb68fece1a6773355493194
--- /dev/null
+++ b/outputs/2026-06-16/13-25-02/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
diff --git a/outputs/2026-06-16/17-30-16/.hydra/config.yaml b/outputs/2026-06-16/17-30-16/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..be4d5f9dd3dbd3c737fe7c1393e9601fbedfc4b3
--- /dev/null
+++ b/outputs/2026-06-16/17-30-16/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-16/17-30-16/.hydra/hydra.yaml b/outputs/2026-06-16/17-30-16/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..dcf0d69c962a4366e3c48e03c1e5a0fc1a3329c5
--- /dev/null
+++ b/outputs/2026-06-16/17-30-16/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-16/17-30-16
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-16/17-30-16/.hydra/overrides.yaml b/outputs/2026-06-16/17-30-16/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d2b95b90f7fae5e2efd9b6828b0f2d8f708a6698
--- /dev/null
+++ b/outputs/2026-06-16/17-30-16/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
diff --git a/outputs/2026-06-16/17-30-16/train.log b/outputs/2026-06-16/17-30-16/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-16/18-42-33/.hydra/config.yaml b/outputs/2026-06-16/18-42-33/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..be4d5f9dd3dbd3c737fe7c1393e9601fbedfc4b3
--- /dev/null
+++ b/outputs/2026-06-16/18-42-33/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: -1
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-16/18-42-33/.hydra/hydra.yaml b/outputs/2026-06-16/18-42-33/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..003a1d117cef9572edf7a643cab5fe9040321693
--- /dev/null
+++ b/outputs/2026-06-16/18-42-33/.hydra/hydra.yaml
@@ -0,0 +1,177 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-16/18-42-33
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-16/18-42-33/.hydra/overrides.yaml b/outputs/2026-06-16/18-42-33/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d2b95b90f7fae5e2efd9b6828b0f2d8f708a6698
--- /dev/null
+++ b/outputs/2026-06-16/18-42-33/.hydra/overrides.yaml
@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
diff --git a/outputs/2026-06-16/18-42-33/train.log b/outputs/2026-06-16/18-42-33/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-18/11-52-39/.hydra/config.yaml b/outputs/2026-06-18/11-52-39/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2cd5336518a94c408ec580dc56c59072f7bdc87e
--- /dev/null
+++ b/outputs/2026-06-18/11-52-39/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube1_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-18/11-52-39/.hydra/hydra.yaml b/outputs/2026-06-18/11-52-39/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c17a90cf6973730e63e98763ca60b7b3d71a46bb
--- /dev/null
+++ b/outputs/2026-06-18/11-52-39/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=1
+ - trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl,trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-18/11-52-39
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-18/11-52-39/.hydra/overrides.yaml b/outputs/2026-06-18/11-52-39/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..30784c9f77368a2f9fea7efff56699ce6eea94fd
--- /dev/null
+++ b/outputs/2026-06-18/11-52-39/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
diff --git a/outputs/2026-06-18/11-52-39/train.log b/outputs/2026-06-18/11-52-39/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-18/12-24-12/.hydra/config.yaml b/outputs/2026-06-18/12-24-12/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d88f3bd9f5654df97b8599bf7b0295db12ac86b2
--- /dev/null
+++ b/outputs/2026-06-18/12-24-12/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-18/12-24-12/.hydra/hydra.yaml b/outputs/2026-06-18/12-24-12/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..93ce84bb5ba75e67e9eb1b52f4f2c1fd958eccbc
--- /dev/null
+++ b/outputs/2026-06-18/12-24-12/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa_rl,trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-18/12-24-12
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-18/12-24-12/.hydra/overrides.yaml b/outputs/2026-06-18/12-24-12/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c2c1cad2ad53076197ce73549abf31438318d0b9
--- /dev/null
+++ b/outputs/2026-06-18/12-24-12/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa_rl
diff --git a/outputs/2026-06-18/12-24-12/train.log b/outputs/2026-06-18/12-24-12/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-18/13-51-23/.hydra/hydra.yaml b/outputs/2026-06-18/13-51-23/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..737864d57e283ecc9da06a0d635e0b0d17fc5d84
--- /dev/null
+++ b/outputs/2026-06-18/13-51-23/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=3
+ - trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=3,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa_rl,trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-18/13-51-23
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-18/13-51-23/.hydra/overrides.yaml b/outputs/2026-06-18/13-51-23/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8ea6690aacfce3355ce938962ff9b78a5c2a3419
--- /dev/null
+++ b/outputs/2026-06-18/13-51-23/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=3
+- trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa_rl
diff --git a/outputs/2026-06-18/13-51-23/train.log b/outputs/2026-06-18/13-51-23/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-22/22-00-14/.hydra/config.yaml b/outputs/2026-06-22/22-00-14/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9fe9522c4cff5679bd3ca8cac8d78dafcf2ca5c4
--- /dev/null
+++ b/outputs/2026-06-22/22-00-14/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube1_withthink_sas
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sas_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-22/22-00-14/.hydra/hydra.yaml b/outputs/2026-06-22/22-00-14/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b0b8890b80cbc4c0c4208df6393793f88df81a8d
--- /dev/null
+++ b/outputs/2026-06-22/22-00-14/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=1
+ - trainer.experiment_name=rubikscube1_withthink_sas
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sas_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sas_rl,trainer.experiment_name=rubikscube1_withthink_sas,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-22/22-00-14
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-22/22-00-14/.hydra/overrides.yaml b/outputs/2026-06-22/22-00-14/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..91be8468d30a8a4d6471c3ce277e4162d8f564d8
--- /dev/null
+++ b/outputs/2026-06-22/22-00-14/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_sas
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sas_rl
diff --git a/outputs/2026-06-22/22-00-14/train.log b/outputs/2026-06-22/22-00-14/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-22/22-11-12/.hydra/config.yaml b/outputs/2026-06-22/22-11-12/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6f3c4b3b8c44a40df82c95ace82017be9f8dd906
--- /dev/null
+++ b/outputs/2026-06-22/22-11-12/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube1_withthink_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-22/22-11-12/.hydra/hydra.yaml b/outputs/2026-06-22/22-11-12/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d2ebe82d0b6753bef2b56d2038309dcb83da3fef
--- /dev/null
+++ b/outputs/2026-06-22/22-11-12/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=1
+ - trainer.experiment_name=rubikscube1_withthink_sa
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sa_rl,trainer.experiment_name=rubikscube1_withthink_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-22/22-11-12
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-22/22-11-12/.hydra/overrides.yaml b/outputs/2026-06-22/22-11-12/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a53c86935332d595769e5723191b244ebce11957
--- /dev/null
+++ b/outputs/2026-06-22/22-11-12/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sa
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sa_rl
diff --git a/outputs/2026-06-22/22-11-12/train.log b/outputs/2026-06-22/22-11-12/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-22/22-32-28/.hydra/config.yaml b/outputs/2026-06-22/22-32-28/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..311e1d8d67476703485a32dc093412dee4986810
--- /dev/null
+++ b/outputs/2026-06-22/22-32-28/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_sas
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sas_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-22/22-32-28/.hydra/hydra.yaml b/outputs/2026-06-22/22-32-28/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d576eb228322b23e2fc1cb4a7e2a5c5abe1c06d2
--- /dev/null
+++ b/outputs/2026-06-22/22-32-28/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_sas
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sas_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sas_rl,trainer.experiment_name=rubikscube2_withthink_sas,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-22/22-32-28
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-22/22-32-28/.hydra/overrides.yaml b/outputs/2026-06-22/22-32-28/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..da2eeddf82bc2011a94d49285ab2fb1c6eb0f157
--- /dev/null
+++ b/outputs/2026-06-22/22-32-28/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_sas
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sas_rl
diff --git a/outputs/2026-06-22/22-32-28/train.log b/outputs/2026-06-22/22-32-28/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-22/22-48-08/.hydra/config.yaml b/outputs/2026-06-22/22-48-08/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..18d87cd5ea7d863b033c6c85af72058e4f1b5c57
--- /dev/null
+++ b/outputs/2026-06-22/22-48-08/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube2_withthink_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 2
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-22/22-48-08/.hydra/hydra.yaml b/outputs/2026-06-22/22-48-08/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d5d5e6f4fb383c96e1859db4a59ff215940de370
--- /dev/null
+++ b/outputs/2026-06-22/22-48-08/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=2
+ - trainer.experiment_name=rubikscube2_withthink_sa
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sa_rl,trainer.experiment_name=rubikscube2_withthink_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-22/22-48-08
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-22/22-48-08/.hydra/overrides.yaml b/outputs/2026-06-22/22-48-08/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..efa65edd8aadb4c43461bb6f7555edc7bdbe16d5
--- /dev/null
+++ b/outputs/2026-06-22/22-48-08/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube2_withthink_sa_rl
diff --git a/outputs/2026-06-22/22-48-08/train.log b/outputs/2026-06-22/22-48-08/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-22/23-59-57/.hydra/config.yaml b/outputs/2026-06-22/23-59-57/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..68c05031fdc35ac45a939aa5b97e330978af4c72
--- /dev/null
+++ b/outputs/2026-06-22/23-59-57/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube3_withthink_sas
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sas_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 3
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-22/23-59-57/.hydra/hydra.yaml b/outputs/2026-06-22/23-59-57/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..024100331023e8f5b2b0fb8a36b41890c6d5a9ee
--- /dev/null
+++ b/outputs/2026-06-22/23-59-57/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas
+ - custom_envs.rubikscube.env_config.scramble_depth=3
+ - trainer.experiment_name=rubikscube3_withthink_sas
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sas_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=3,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sas_rl,trainer.experiment_name=rubikscube3_withthink_sas,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-22/23-59-57
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-22/23-59-57/train.log b/outputs/2026-06-22/23-59-57/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-23/00-14-05/.hydra/config.yaml b/outputs/2026-06-23/00-14-05/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8842672def67ba607884be061b8b0265a2f32c7e
--- /dev/null
+++ b/outputs/2026-06-23/00-14-05/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 200
+ project_name: ragen
+ experiment_name: rubikscube3_withthink_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 200
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 3
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-23/00-14-05/.hydra/hydra.yaml b/outputs/2026-06-23/00-14-05/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..20d86a6375204f3127524cd2828fd119d47e379a
--- /dev/null
+++ b/outputs/2026-06-23/00-14-05/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=200
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=3
+ - trainer.experiment_name=rubikscube3_withthink_sa
+ - trainer.save_freq=200
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=3,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sa_rl,trainer.experiment_name=rubikscube3_withthink_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-23/00-14-05
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-23/00-14-05/.hydra/overrides.yaml b/outputs/2026-06-23/00-14-05/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3cb961e2364a3e22ea63872f2e34e262f1d95ef6
--- /dev/null
+++ b/outputs/2026-06-23/00-14-05/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sa
+- custom_envs.rubikscube.env_config.scramble_depth=3
+- trainer.experiment_name=rubikscube3_withthink_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube3_withthink_sa_rl
diff --git a/outputs/2026-06-23/00-14-05/train.log b/outputs/2026-06-23/00-14-05/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-23/14-24-28/.hydra/config.yaml b/outputs/2026-06-23/14-24-28/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d572a314fc18de2fde27ba413752320de8dc1093
--- /dev/null
+++ b/outputs/2026-06-23/14-24-28/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 50
+ project_name: ragen
+ experiment_name: rubikscube1_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 50
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-23/14-24-28/.hydra/hydra.yaml b/outputs/2026-06-23/14-24-28/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1c69691f7358f69663cae7fc89e3b3ae33434b77
--- /dev/null
+++ b/outputs/2026-06-23/14-24-28/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=50
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=1
+ - trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+ - trainer.save_freq=50
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl,trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.save_freq=50,trainer.total_training_steps=50
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-23/14-24-28
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-23/14-24-28/.hydra/overrides.yaml b/outputs/2026-06-23/14-24-28/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2ab321463fdd102e95777e56bcccbeec360d4fd1
--- /dev/null
+++ b/outputs/2026-06-23/14-24-28/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=50
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+- trainer.save_freq=50
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
diff --git a/outputs/2026-06-23/14-24-28/train.log b/outputs/2026-06-23/14-24-28/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-23/14-31-50/.hydra/config.yaml b/outputs/2026-06-23/14-31-50/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d572a314fc18de2fde27ba413752320de8dc1093
--- /dev/null
+++ b/outputs/2026-06-23/14-31-50/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 50
+ project_name: ragen
+ experiment_name: rubikscube1_withthink_fulltrajc_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 50
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-23/14-31-50/.hydra/hydra.yaml b/outputs/2026-06-23/14-31-50/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..358cfc21bb3a856a74670462f7305499817254ff
--- /dev/null
+++ b/outputs/2026-06-23/14-31-50/.hydra/hydra.yaml
@@ -0,0 +1,179 @@
+hydra:
+ run:
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ sweep:
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+ subdir: ${hydra.job.num}
+ launcher:
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+ sweeper:
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+ max_batch_size: null
+ params: null
+ help:
+ app_name: ${hydra.job.name}
+ header: '${hydra.help.app_name} is powered by Hydra.
+
+ '
+ footer: 'Powered by Hydra (https://hydra.cc)
+
+ Use --hydra-help to view Hydra specific help
+
+ '
+ template: '${hydra.help.header}
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (group=option)
+
+
+ $APP_CONFIG_GROUPS
+
+
+ == Config ==
+
+ Override anything in the config (foo.bar=value)
+
+
+ $CONFIG
+
+
+ ${hydra.help.footer}
+
+ '
+ hydra_help:
+ template: 'Hydra (${hydra.runtime.version})
+
+ See https://hydra.cc for more info.
+
+
+ == Flags ==
+
+ $FLAGS_HELP
+
+
+ == Configuration groups ==
+
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+ to command line)
+
+
+ $HYDRA_CONFIG_GROUPS
+
+
+ Use ''--cfg hydra'' to Show the Hydra config.
+
+ '
+ hydra_help: ???
+ hydra_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][HYDRA] %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ root:
+ level: INFO
+ handlers:
+ - console
+ loggers:
+ logging_example:
+ level: DEBUG
+ disable_existing_loggers: false
+ job_logging:
+ version: 1
+ formatters:
+ simple:
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+ handlers:
+ console:
+ class: logging.StreamHandler
+ formatter: simple
+ stream: ext://sys.stdout
+ file:
+ class: logging.FileHandler
+ formatter: simple
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+ root:
+ level: INFO
+ handlers:
+ - console
+ - file
+ disable_existing_loggers: false
+ env: {}
+ mode: RUN
+ searchpath: []
+ callbacks: {}
+ output_subdir: .hydra
+ overrides:
+ hydra:
+ - hydra.mode=RUN
+ task:
+ - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+ - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+ - actor_rollout_ref.rollout.rollout_filter_value=0.9
+ - trainer.total_training_steps=50
+ - trainer.n_gpus_per_node=8
+ - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+ - custom_envs.rubikscube.env_config.scramble_depth=1
+ - trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+ - trainer.save_freq=50
+ - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+ job:
+ name: train
+ chdir: null
+ override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl,trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.save_freq=50,trainer.total_training_steps=50
+ id: ???
+ num: ???
+ config_name: _10_rubikscube
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.3.2
+ version_base: '1.3'
+ cwd: /mnt/general/wanghy/RAGEN_v2
+ config_sources:
+ - path: hydra.conf
+ schema: pkg
+ provider: hydra
+ - path: /mnt/general/wanghy/RAGEN_v2/config
+ schema: file
+ provider: main
+ - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+ schema: file
+ provider: command-line
+ - path: ''
+ schema: structured
+ provider: schema
+ output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-23/14-31-50
+ choices:
+ reward_model: dp_reward_model
+ critic: dp_critic
+ critic/../engine@critic.model.fsdp_config: fsdp
+ critic/../optim@critic.optim: fsdp
+ model@actor_rollout_ref.model: hf_model
+ rollout@actor_rollout_ref.rollout: rollout
+ ref@actor_rollout_ref.ref: dp_ref
+ ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+ data: legacy_data
+ actor@actor_rollout_ref.actor: dp_actor
+ actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+ actor/../optim@actor_rollout_ref.actor.optim: fsdp
+ hydra/env: default
+ hydra/callbacks: null
+ hydra/job_logging: default
+ hydra/hydra_logging: default
+ hydra/hydra_help: default
+ hydra/help: default
+ hydra/sweeper: basic
+ hydra/launcher: basic
+ hydra/output: default
+ verbose: false
diff --git a/outputs/2026-06-23/14-31-50/.hydra/overrides.yaml b/outputs/2026-06-23/14-31-50/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2ab321463fdd102e95777e56bcccbeec360d4fd1
--- /dev/null
+++ b/outputs/2026-06-23/14-31-50/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=50
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+- trainer.save_freq=50
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
diff --git a/outputs/2026-06-23/14-31-50/train.log b/outputs/2026-06-23/14-31-50/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-23/14-51-00/.hydra/config.yaml b/outputs/2026-06-23/14-51-00/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f4f782250d818c9cb21788f050e92589f2133fa0
--- /dev/null
+++ b/outputs/2026-06-23/14-51-00/.hydra/config.yaml
@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+ actor:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-06
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ _target_: verl.workers.config.FSDPActorConfig
+ strategy: fsdp
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: false
+ ppo_max_token_len_per_gpu: 16384
+ clip_ratio: 0.2
+ clip_ratio_low: 0.2
+ clip_ratio_high: 0.28
+ freeze_vision_tower: false
+ policy_loss:
+ _target_: verl.workers.config.PolicyLossConfig
+ loss_mode: vanilla
+ clip_cov_ratio: 0.0002
+ clip_cov_lb: 1.0
+ clip_cov_ub: 5.0
+ kl_cov_ratio: 0.0002
+ ppo_kl_coef: 0.1
+ clip_ratio_c: 3.0
+ loss_agg_mode: token-mean
+ entropy_coeff: 0.001
+ tis_imp_ratio_cap: -1
+ use_kl_loss: false
+ use_torch_compile: true
+ kl_loss_coef: 0.0
+ kl_loss_type: kl
+ ppo_epochs: 1
+ shuffle: false
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ grad_clip: 1.0
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+ use_ref: true
+ grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+ filter_loss_scaling: none
+ ref:
+ strategy: ${actor_rollout_ref.actor.strategy}
+ use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ model: null
+ ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+ entropy_from_logits_with_chunking: false
+ entropy_checkpointing: false
+ rollout:
+ _target_: verl.workers.config.RolloutConfig
+ name: vllm
+ mode: sync
+ temperature: 1
+ top_k: -1
+ top_p: 1
+ prompt_length: 1
+ response_length: 500
+ dtype: bfloat16
+ gpu_memory_utilization: 0.7
+ ignore_eos: false
+ enforce_eager: true
+ cudagraph_capture_sizes: null
+ free_cache_engine: true
+ tensor_model_parallel_size: 1
+ data_parallel_size: 1
+ expert_parallel_size: 1
+ max_num_batched_tokens: 16384
+ max_model_len: 16384
+ max_num_seqs: 1024
+ enable_chunked_prefill: true
+ enable_prefix_caching: true
+ load_format: auto
+ log_prob_micro_batch_size: null
+ log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+ log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+ disable_log_stats: true
+ do_sample: true
+ 'n': 1
+ over_sample_rate: 0
+ multi_stage_wake_up: false
+ engine_kwargs:
+ vllm: {}
+ sglang: {}
+ val_kwargs:
+ _target_: verl.workers.config.SamplingConfig
+ top_k: -1
+ top_p: 1.0
+ temperature: 0.5
+ 'n': 1
+ do_sample: true
+ multi_turn:
+ _target_: verl.workers.config.MultiTurnConfig
+ enable: false
+ max_assistant_turns: null
+ tool_config_path: null
+ max_user_turns: null
+ max_parallel_calls: 1
+ max_tool_response_length: 256
+ tool_response_truncate_side: middle
+ interaction_config_path: null
+ use_inference_chat_template: false
+ tokenization_sanity_check_mode: strict
+ format: hermes
+ num_repeat_rollouts: null
+ calculate_log_probs: false
+ agent:
+ _target_: verl.workers.config.AgentLoopConfig
+ num_workers: 8
+ agent_loop_config_path: null
+ custom_async_server:
+ _target_: verl.workers.config.CustomAsyncServerConfig
+ path: null
+ name: null
+ update_weights_bucket_megabytes: 512
+ trace:
+ _target_: verl.workers.config.TraceConfig
+ backend: null
+ token2text: false
+ skip_rollout: false
+ skip_dump_dir: /tmp/rollout_dump
+ skip_tokenizer_init: true
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+ all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+ ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ layered_summon: false
+ rollout_filter_value: 0.9
+ rollout_filter_strategy: top_p
+ rollout_filter_type: largest
+ rollout_filter_include_zero: true
+ rollout_filter_top_p_prob_mode: linear
+ rollout_filter_selection_eps: 0.01
+ rollout_filter_empty_stop_steps: 5
+ rollout_filter_metric: reward_variance
+ gradient_analysis_num_buckets: 6
+ gradient_analysis_bucket_mode: quantile
+ model:
+ _target_: verl.workers.config.HFModelConfig
+ path: ${model_path}
+ hf_config_path: null
+ tokenizer_path: null
+ use_shm: false
+ trust_remote_code: false
+ custom_chat_template: null
+ external_lib: null
+ override_config: {}
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ exclude_modules: null
+ use_liger: false
+ use_fused_kernels: false
+ fused_kernel_options:
+ impl_backend: torch
+ hybrid_engine: true
+ nccl_timeout: 600
+data:
+ tokenizer: null
+ use_shm: false
+ train_files: ~/data/rlhf/gsm8k/train.parquet
+ val_files: ~/data/rlhf/gsm8k/test.parquet
+ prompt_key: prompt
+ reward_fn_key: data_source
+ max_prompt_length: null
+ max_response_length: null
+ train_batch_size: null
+ val_batch_size: null
+ return_raw_input_ids: false
+ return_raw_chat: false
+ return_full_prompt: false
+ shuffle: true
+ dataloader_num_workers: 8
+ validation_shuffle: false
+ filter_overlong_prompts: false
+ filter_overlong_prompts_workers: 1
+ truncation: error
+ image_key: images
+ video_key: videos
+ trust_remote_code: false
+ custom_cls:
+ path: null
+ name: null
+ return_multi_modal_inputs: true
+ sampler:
+ class_path: null
+ class_name: null
+ datagen:
+ path: null
+ name: null
+ apply_chat_template_kwargs: {}
+critic:
+ optim:
+ _target_: verl.workers.config.FSDPOptimizerConfig
+ lr: 1.0e-05
+ lr_warmup_steps_ratio: 0.0
+ total_training_steps: -1
+ weight_decay: 0.01
+ lr_warmup_steps: -1
+ betas:
+ - 0.9
+ - 0.999
+ clip_grad: 1.0
+ min_lr_ratio: 0.0
+ num_cycles: 0.5
+ warmup_style: constant
+ model:
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ optimizer_offload: false
+ offload_policy: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ model_dtype: fp32
+ use_orig_params: false
+ ulysses_sequence_parallel_size: 1
+ entropy_from_logits_with_chunking: false
+ use_torch_compile: true
+ entropy_checkpointing: false
+ forward_only: false
+ strategy: fsdp
+ path: ${model_path}
+ tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+ override_config: {}
+ external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+ trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+ _target_: verl.workers.config.FSDPCriticModelCfg
+ use_shm: false
+ enable_gradient_checkpointing: true
+ enable_activation_offload: false
+ use_remove_padding: false
+ lora_rank: ${lora.rank}
+ lora_alpha: ${lora.alpha}
+ target_modules: ${lora.target_modules}
+ _target_: verl.workers.config.FSDPCriticConfig
+ rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+ strategy: fsdp
+ enable: null
+ ppo_mini_batch_size: ${ppo_mini_batch_size}
+ ppo_micro_batch_size: null
+ ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+ ppo_max_token_len_per_gpu: 32768
+ forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+ ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+ shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+ cliprange_value: 0.5
+ loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+ checkpoint:
+ _target_: verl.trainer.config.CheckpointConfig
+ save_contents:
+ - model
+ - optimizer
+ - extra
+ load_contents: ${.save_contents}
+ async_save: false
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+ npu:
+ _target_: verl.utils.profiler.config.NPUToolConfig
+ contents: []
+ level: level1
+ analysis: true
+ discrete: false
+ torch:
+ _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+ step_start: 0
+ step_end: null
+ torch_memory:
+ _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+ trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+ stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+ forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+ forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+ ulysses_sequence_parallel_size: 1
+ grad_clip: 1.0
+reward_model:
+ enable: false
+ enable_resource_pool: false
+ n_gpus_per_node: 0
+ nnodes: 0
+ strategy: fsdp
+ model:
+ input_tokenizer: ${actor_rollout_ref.model.path}
+ path: ~/models/FsfairX-LLaMA3-RM-v0.1
+ external_lib: ${actor_rollout_ref.model.external_lib}
+ trust_remote_code: false
+ use_shm: false
+ use_remove_padding: false
+ use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+ fsdp_config:
+ _target_: verl.workers.config.FSDPEngineConfig
+ wrap_policy:
+ min_num_params: 0
+ param_offload: false
+ reshard_after_forward: true
+ fsdp_size: -1
+ forward_prefetch: false
+ micro_batch_size: null
+ micro_batch_size_per_gpu: null
+ max_length: null
+ use_dynamic_bsz: ${critic.use_dynamic_bsz}
+ forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+ reward_manager: naive
+ launch_reward_fn_async: false
+ sandbox_fusion:
+ url: null
+ max_concurrent: 64
+ memory_limit_mb: 1024
+ profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: ${oc.select:global_profiler.tool,null}
+ enable: false
+ all_ranks: false
+ ranks: []
+ save_path: ${oc.select:global_profiler.save_path,null}
+ tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+ ulysses_sequence_parallel_size: 1
+custom_reward_function:
+ path: null
+ name: compute_score
+algorithm:
+ _target_: verl.trainer.config.AlgoConfig
+ gamma: 1.0
+ lam: 1.0
+ adv_estimator: gae
+ norm_adv_by_std_in_grpo: true
+ use_kl_in_reward: false
+ kl_penalty: kl
+ kl_ctrl:
+ _target_: verl.trainer.config.KLControlConfig
+ type: fixed
+ kl_coef: 0.0
+ horizon: 10000
+ target_kl: 0.1
+ use_pf_ppo: false
+ pf_ppo:
+ reweight_method: pow
+ weight_pow: 2.0
+ high_level_gamma: 0.95
+ bi_level_gae: false
+ zero_task_advantage: false
+ soft_advantage_reweight: false
+trainer:
+ balance_batch: true
+ total_epochs: 30
+ total_training_steps: 50
+ project_name: ragen
+ experiment_name: rubikscube1_withthink_sa
+ logger:
+ - console
+ - wandb
+ log_val_generations: 0
+ rollout_data_dir: null
+ validation_data_dir: null
+ nnodes: 1
+ n_gpus_per_node: 8
+ save_freq: 50
+ esi_redundant_time: 0
+ resume_mode: auto
+ resume_from_path: null
+ val_before_train: true
+ val_only: false
+ test_freq: 10
+ critic_warmup: 0
+ default_hdfs_dir: null
+ del_local_ckpt_after_load: false
+ default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sa_rl
+ max_actor_ckpt_to_keep: 1
+ max_critic_ckpt_to_keep: 1
+ ray_wait_register_center_timeout: 300
+ device: cuda
+ use_legacy_worker_impl: auto
+ local_log_dir: results/
+ validation_steps: 1
+ generations_to_log_to_wandb:
+ val: 20
+ log_group_rv_table: false
+ gradient_analysis_mode: false
+ gradient_analysis_every: 50
+ gradient_analysis_env_groups: null
+ gradient_analysis_group_size: null
+ gradient_analysis_log_prefilter: false
+ gradient_analysis_only: false
+ exit_after_gradient_analysis: false
+global_profiler:
+ _target_: verl.utils.profiler.ProfilerConfig
+ tool: null
+ steps: null
+ profile_continuous_steps: false
+ save_path: outputs/profile
+ global_tool_config:
+ nsys:
+ _target_: verl.utils.profiler.config.NsightToolConfig
+ discrete: false
+ controller_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ worker_nsight_options:
+ trace: cuda,nvtx,cublas,ucx
+ cuda-memory-usage: 'true'
+ cuda-graph-trace: graph
+ capture-range: cudaProfilerApi
+ capture-range-end: null
+ kill: none
+ torch_memory:
+ trace_alloc_max_entries: 100000
+ stack_depth: 32
+ context: all
+ stacks: all
+ kw_args: {}
+ray_kwargs:
+ ray_init:
+ num_cpus: null
+ timeline_json_file: null
+custom_envs:
+ SimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+ \ when reasoning:\n1. First compare the box position with the target position;\
+ \ the useful push directions are usually the directions that reduce their row/column\
+ \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+ \ push direction. A move that only repositions the player can be useful if it\
+ \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+ \ dead end unless that square is the target or clearly on the only path to the\
+ \ target.\n4. Prefer short plans that move the single box steadily toward the\
+ \ target; avoid wandering moves that do not improve player position or box position.\n\
+ 5. If the box and target are aligned in the same row or column, try to keep\
+ \ the box on that line and push along it.\n6. If they are not aligned, first\
+ \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+ 7. Check that after each push, the player can still reach the next required\
+ \ pushing side of the box.\n8. Output only the required XML-like format and\
+ \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+ \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+ \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box. \nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 2
+ max_steps: 100
+ LargerSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 8
+ dim_y: 8
+ num_boxes: 2
+ max_steps: 100
+ search_depth: 10
+ SokobanDifferentGridVocab:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+ \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+ \ you can push it by moving in the same direction. \nYou cannot push a box through\
+ \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+ \ like Right || Right || Up\n"
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ search_depth: 30
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ grid_lookup:
+ 0: W
+ 1: .
+ 2: G
+ 3: C
+ 4: B
+ 5: A
+ 6: '@'
+ grid_vocab:
+ W: wall
+ .: empty
+ G: target
+ C: box on target
+ B: box
+ A: player
+ '@': player on target
+ CoordSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 20
+ env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+ \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+ \ the zero-indexed coordinates of the player, each box, and each target. \n\
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+ \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+ \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+ \ pull a box.\nThe answer should be a sequence of actions, like Right\
+ \ || Right || Up.\n"
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ observation_format: grid_coord
+ VisualSimpleSokoban:
+ env_type: sokoban
+ max_actions_per_traj: 10
+ env_instruction: You are solving the Sokoban puzzle. You are the player and you
+ need to push all boxes to targets. When you are right next to a box, you can
+ push it by moving in the same direction. You cannot push a box through a wall,
+ and you cannot pull a box. The answer should be a sequence of actions, like
+ Right || Right || Up
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ dim_x: 6
+ dim_y: 6
+ num_boxes: 1
+ max_steps: 100
+ render_mode: rgb_array
+ Alfworld:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_in_distribution
+ AlfworldOOD:
+ env_type: alfworld
+ max_actions_per_traj: 50
+ parallel_friendly: false
+ max_workers: 1
+ env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+ Complete household tasks by navigating and interacting with objects.
+
+
+ You should first reason step-by-step about the current situation. This reasoning
+ process MUST be enclosed within tags.
+
+ Once you''ve finished your reasoning, you should choose an admissible action
+ for current step and present it within ... tags.
+
+ '
+ max_tokens: 512
+ env_config:
+ eval_dataset: eval_out_of_distribution
+ Countdown:
+ env_type: countdown
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving the Countdown puzzle. You should use the num
+ list to create an equation that equals the target. Example answer format:
+ To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+ = 4. So the answer is 2 + 5 - 3 = 4. 2 + 5 - 3'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config: null
+ Bandit:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: train
+ BanditTest:
+ env_type: bandit
+ max_actions_per_traj: 1
+ env_instruction: ''
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ split: test
+ DeepCoder:
+ env_type: deepcoder
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving a coding task. Provide a complete Python function
+ solution only. Format: ...'
+ max_tokens: 8000
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 1
+ FrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+ go to the target. You may move to the unintended direction due to the slippery
+ ice. Example answer format: To forbid the hole and go to the target,
+ I should go left then go up.Left || Up'
+ max_tokens: 100
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ success_rate: 0.8
+ CoordFrozenLake:
+ env_type: frozen_lake
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+ both a symbol grid and zero-indexed coordinates for the start, goal, player,
+ and any holes.
+
+ Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+ (5, 5).
+
+ Beware that the ice is slippery, so the agent might slide and end up in an unintended
+ tile.
+
+ Respond with a sequence of actions such as Left || Up || Up.
+
+ '
+ max_tokens: 120
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ observation_format: grid_coord
+ success_rate: 0.8
+ MetamathQA:
+ env_type: metamathqa
+ max_actions_per_traj: 1
+ env_instruction: 'You are solving Math problems. '
+ max_tokens: 100
+ env_config: null
+ WebShopFull:
+ env_type: webshop
+ max_actions_per_traj: 15
+ env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+ environment.
+ max_tokens: 200
+ env_config:
+ dataset: full
+ WebShop:
+ env_type: webshop
+ max_actions_per_traj: 9
+ env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+ a product that close to the production description. You need to search, read
+ the search results, pick a product, choose the size and color and buy. You should
+ only choose action from the available actions list provided later. Example
+ process: I need a gingko light and 20x20 pillow cover that is hand painted.
+ First search[gingko light 20x20 pillow cover hand painted], answer format: search[blanket
+ with fleece throw]. Valid answer is search[] or click[].'
+ max_tokens: 200
+ env_config:
+ dataset: small
+ Lean:
+ env_type: lean
+ max_actions_per_traj: 30
+ env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+ propose a sequence of tactics that completes the proof. Think step by step about
+ which tactics to apply next. Provide tactics separated by '||', for example
+ intro || simp || rfl.
+ max_tokens: 512
+ parallel_friendly: true
+ max_workers: 32
+ env_config: null
+ SimpleSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 20
+ env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+ when reasoning:
+
+ 1. In , explain the constraint logic behind the move, not just the final
+ placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+ 2. Treat each move as a constraint-preserving placement: place a number only
+ if it does not already appear in the same row, column, or 2x2 box.
+
+ 3. First look for highly forced cells. If an empty cell has only one legal candidate
+ after checking its row, column, and box, fill it immediately and explain why
+ other numbers are excluded.
+
+ 4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+ numbers. If a missing number can go in only one empty position within that unit,
+ place it there and state that unit-level reason.
+
+ 5. Prefer moves that reduce uncertainty and create new forced cells for the
+ next turn. A good move should make the remaining puzzle more constrained, not
+ more ambiguous.
+
+ 6. Solve incrementally: choose exactly one placement, explain it briefly in
+ , then output that one move in .
+
+ 7. Never modify bracketed initial cells or already-filled cells. Only place
+ numbers into dots.
+
+ 8. Avoid exploratory guesses when a forced move exists. In this environment,
+ reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+ 9. If a previous move was invalid or the board did not change, do not repeat
+ the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+ choice.
+
+ 10. Use row, column, and box agreement as confidence: the strongest placements
+ are those supported by multiple constraints at once.
+
+ 11. Keep concise but meaningful: identify the target cell, list or compare
+ its legal candidates, and give the decisive constraint.
+
+ 12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+ You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+ and 2x2 box contains the numbers 1-4 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 1 at row 2 col 3
+
+ Always output: [brief constraint-based reasoning]
+ [one placement]
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 4
+ difficulty: easy
+ render_format: with_feedback
+ show_conflicts: false
+ show_valid_numbers: false
+ max_steps: 20
+ MediumSudoku:
+ env_type: sudoku
+ max_actions_per_traj: 30
+ env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+ row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+ Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+ shown as dots (.).
+
+ Place numbers one at a time using the format: place 5 at row 2 col 3
+ or 2,3,5
+
+ The environment will provide feedback on valid/invalid moves and show conflicts
+ if any occur.
+
+ '
+ max_tokens: 150
+ parallel_friendly: false
+ max_workers: 32
+ env_config:
+ grid_size: 9
+ difficulty: medium
+ render_format: with_feedback
+ show_conflicts: true
+ show_valid_numbers: true
+ max_steps: 81
+ SearchQA:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ SearchQAMock:
+ env_type: search
+ max_actions_per_traj: 10
+ env_instruction: "You are a search agent answering questions by searching for\
+ \ information.\nUse search[your query] to find relevant documents, and finish[your\
+ \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+ \ about the current situation. This reasoning process MUST be enclosed within\
+ \ tags.\nThen provide your action within ...\
+ \ tags.\n\nExamples:\n I need to find information about Ben Platt's\
+ \ father.search[Ben Platt father parent]\n Based\
+ \ on the search results, Ben Platt's father is Henry Platt.finish[Henry\
+ \ Platt]\n"
+ max_tokens: 300
+ parallel_friendly: true
+ max_workers: 32
+ env_config:
+ max_steps: 10
+ max_search_results: 5
+ mock_mode: true
+ game_2048:
+ env_type: game_2048
+ max_actions_per_traj: 700
+ env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+ by sliding Up, Right, Down, or Left.
+
+ If a move is invalid (no tiles move), a small penalty is applied. Respond with
+ a single action.
+
+ Example: Up
+
+ '
+ max_tokens: 8192
+ env_config: null
+ rubikscube:
+ env_type: rubikscube
+ max_actions_per_traj: 10
+ env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+ is to restore the cube so that each of the faces consists of a single, unique
+ color.
+
+ Available actions use standard Singmaster notation for face rotations: U, U'',
+ D, D'', L, L'', R, R'', F, F'', B, B''.
+
+ - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+ - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+ prime ('') means 90° counter-clockwise (e.g., "R''").
+
+ Respond with a sequence of actions separated by "||".
+
+ Example: U
+
+ '
+ max_tokens: 96
+ env_config:
+ scramble_depth: 1
+ max_steps: 7
+ render_mode: text
+system:
+ CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+ train: 10000
+ val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+ rank: 0
+ alpha: 64
+ target_modules: all-linear
+agent_proxy:
+ context_window_mode: full
+ max_context_window: 5
+ batch_adjust_mode: copy
+ max_turn: 10
+ action_sep: '||'
+ max_actions_per_turn: 4
+ use_turn_scores: false
+ enable_think: true
+ reward_normalization:
+ grouping: state
+ method: identity
+collapse_detection:
+ compute_freq: 5
+ micro_batch_size: 128
+ first_turn_enabled: true
+ multi_turn_enabled: true
+ num_samples: 64
+es_manager:
+ format_penalty: -0.1
+ train:
+ env_groups: 8
+ group_size: 16
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 8
+ val:
+ env_groups: 512
+ group_size: 1
+ env_configs:
+ tags:
+ - rubikscube
+ n_groups:
+ - 512
+ctx_manager:
+ generation:
+ gen_config:
+ response_length: ${actor_rollout_ref.rollout.response_length}
+ temperature: ${actor_rollout_ref.rollout.temperature}
+ top_p: ${actor_rollout_ref.rollout.top_p}
+ top_k: ${actor_rollout_ref.rollout.top_k}
+ kwargs: null
diff --git a/outputs/2026-06-23/14-51-00/.hydra/overrides.yaml b/outputs/2026-06-23/14-51-00/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..780ec0aedad0f87e4e784d15030303637dfd33ef
--- /dev/null
+++ b/outputs/2026-06-23/14-51-00/.hydra/overrides.yaml
@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=50
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sa
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_sa
+- trainer.save_freq=50
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_sa_rl
diff --git a/outputs/2026-06-23/14-51-00/train.log b/outputs/2026-06-23/14-51-00/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/outputs/2026-06-23/15-19-48/train.log b/outputs/2026-06-23/15-19-48/train.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/patches/verl_checkpoint_resharding/README.md b/patches/verl_checkpoint_resharding/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..12fef4842c5e5ca31e48a0f83743319746db9362
--- /dev/null
+++ b/patches/verl_checkpoint_resharding/README.md
@@ -0,0 +1,35 @@
+# FSDP Checkpoint Resharding Patch
+
+## Problem
+
+verl's `FSDPCheckpointManager` saves checkpoints as `model_world_size_{N}_rank_{R}.pt`. When resuming with a **different number of GPUs** than the original training run, the checkpoint files don't match and loading fails:
+
+```
+FileNotFoundError: model_world_size_4_rank_1.pt
+# (checkpoint was saved with 1 GPU as model_world_size_1_rank_0.pt)
+```
+
+## Fix
+
+This patched `fsdp_checkpoint_manager.py` adds automatic resharding: when the expected checkpoint file doesn't exist but a `model_world_size_1_rank_0.pt` is found, it loads the full state dict and lets FSDP reshard across the current world size.
+
+### What changes:
+
+1. **Model loading**: Detects world_size mismatch, switches from `SHARDED_STATE_DICT` to `FULL_STATE_DICT` loading mode so FSDP can reshard automatically
+2. **Optimizer**: Skipped during resharding (optimizer state is world_size-specific and must reinitialize)
+3. **Extra state** (lr_scheduler, rng): Falls back to the 1-GPU file if available, or skips gracefully
+
+## How to Apply
+
+Copy the patched file over the verl submodule file:
+
+```bash
+cp patches/verl_checkpoint_resharding/fsdp_checkpoint_manager.py \
+ verl/verl/utils/checkpoint/fsdp_checkpoint_manager.py
+```
+
+## Limitations
+
+- Only supports resharding **from 1 GPU** to N GPUs (not arbitrary M→N)
+- Optimizer state is not transferred (will reinitialize from scratch)
+- LR scheduler state may not transfer if extra state was not saved
diff --git a/ragen/__init__.py b/ragen/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e041332d026eb0b7bf64753cc1cdd2b5c5c225a1
--- /dev/null
+++ b/ragen/__init__.py
@@ -0,0 +1,6 @@
+"""RAGEN package initialisation."""
+
+from ragen.patches import apply_omega_conf_patch
+
+# Ensure VERL config instantiation accepts RAGEN-specific extensions.
+apply_omega_conf_patch()
diff --git a/ragen/__pycache__/__init__.cpython-310.pyc b/ragen/__pycache__/__init__.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..30bb098a78dfe35cb2c4b48ddcd06d55501a1e91
Binary files /dev/null and b/ragen/__pycache__/__init__.cpython-310.pyc differ
diff --git a/ragen/env/__pycache__/base.cpython-310.pyc b/ragen/env/__pycache__/base.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..d2dab25afd12e228be452ed677ea40845b550d6c
Binary files /dev/null and b/ragen/env/__pycache__/base.cpython-310.pyc differ
diff --git a/ragen/env/alfworld/env.py b/ragen/env/alfworld/env.py
new file mode 100644
index 0000000000000000000000000000000000000000..81af4e10f669153294788228e29c258c3d930584
--- /dev/null
+++ b/ragen/env/alfworld/env.py
@@ -0,0 +1,248 @@
+"""
+This is the environment for the ALFRED dataset.
+author: Qineng Wang
+date: 2025-03-30
+
+Modified to match verl-agent AlfWorld implementation:
+- Dynamic mode switching between train/val
+- Simplified reward: score * won
+- Admissible actions included in observation
+"""
+import os
+import random
+import textworld
+import textworld.gym
+import numpy as np
+from alfworld.agents.environment.alfred_tw_env import AlfredTWEnv, AlfredDemangler, AlfredInfos
+from ragen.env.base import BaseLanguageBasedEnv
+from ragen.env.alfworld.config import AlfredEnvConfig
+from ragen.env.alfworld.utils import load_config
+
+_RAW_ENV_CACHE = {}
+
+class AlfredTXTEnv(BaseLanguageBasedEnv):
+
+ # Mode mapping: RAGEN mode -> AlfWorld train_eval
+ MODE_MAP = {
+ 'train': 'train',
+ 'val': None, # Will use config.eval_dataset
+ 'test': None, # Will use config.eval_dataset
+ }
+
+ def __init__(self, config: AlfredEnvConfig = AlfredEnvConfig(), mode='train'):
+ """
+ Initialize AlfWorld environment.
+
+ Args:
+ config: AlfredEnvConfig instance
+ mode: 'train' or 'val' - determines which dataset split to use
+ """
+ super().__init__()
+ self.config = config
+ self.raw_env_config = load_config(self.config.config_file)
+
+ # Map RAGEN mode to AlfWorld train_eval
+ self.current_mode = mode
+ self._alfworld_mode = self._get_alfworld_mode(mode)
+
+ # Initialize raw environment
+ self.raw_env = self._get_cached_raw_env(self._alfworld_mode)
+ self.num_games = self.raw_env.num_games
+ self.game_files = list(self.raw_env.game_files)
+
+ self.alfred_env = None
+ self.current_game_file = None
+ self.render_cache = None
+ self.available_actions = None
+ self.render_mode = self.config.render_mode
+ assert self.render_mode == 'text'
+
+ def _get_alfworld_mode(self, mode: str) -> str:
+ """Convert RAGEN mode to AlfWorld train_eval string."""
+ if mode == 'train':
+ return 'train'
+ else:
+ # Use eval_dataset from config for val/test modes
+ return self.config.eval_dataset
+
+ def _get_cached_raw_env(self, alfworld_mode: str) -> AlfredTWEnv:
+ cache_key = (os.path.abspath(self.config.config_file), alfworld_mode)
+ raw_env = _RAW_ENV_CACHE.get(cache_key)
+ if raw_env is None:
+ raw_env = AlfredTWEnv(config=self.raw_env_config, train_eval=alfworld_mode)
+ _RAW_ENV_CACHE[cache_key] = raw_env
+ return raw_env
+
+ def _reinitialize_for_mode(self, mode: str):
+ """Reinitialize the environment when mode changes."""
+ new_alfworld_mode = self._get_alfworld_mode(mode)
+
+ if new_alfworld_mode != self._alfworld_mode:
+ # Close existing environment
+ if hasattr(self, 'alfred_env') and self.alfred_env is not None:
+ try:
+ self.alfred_env.close()
+ except Exception:
+ pass
+
+ # Reinitialize with new mode
+ self._alfworld_mode = new_alfworld_mode
+ self.current_mode = mode
+ self.raw_env = self._get_cached_raw_env(self._alfworld_mode)
+ self.num_games = self.raw_env.num_games
+ self.game_files = list(self.raw_env.game_files)
+ self.alfred_env = None
+
+ def reset(self, seed=None, mode=None):
+ """
+ Reset the environment with a specific seed.
+
+ Args:
+ seed: Random seed for game selection
+ mode: 'train', 'val', or 'test' - if different from current mode,
+ reinitializes the environment with the new dataset split
+
+ Returns:
+ observation: Initial observation text with admissible actions
+ """
+ try:
+ # Handle mode switching dynamically
+ if mode is not None and mode != self.current_mode:
+ self._reinitialize_for_mode(mode)
+ elif mode is not None:
+ self.current_mode = mode
+
+ # Select game based on mode
+ if self.current_mode == "test":
+ if seed is None:
+ raise ValueError("Seed must be provided in test mode.")
+ selected_game = self.game_files[seed % len(self.game_files)]
+ else:
+ if seed is not None:
+ np.random.seed(seed)
+ random.seed(seed)
+ game_idx = seed % len(self.game_files)
+ selected_game = self.game_files[game_idx]
+ else:
+ selected_game = random.choice(self.game_files)
+
+ self.current_game_file = selected_game
+
+ if hasattr(self, 'alfred_env') and self.alfred_env is not None:
+ try:
+ self.alfred_env.close()
+ except Exception:
+ pass
+
+ request_infos = textworld.EnvInfos(won=True, admissible_commands=True, extras=["gamefile"])
+ wrappers = [AlfredDemangler(), AlfredInfos()]
+ max_steps = self.raw_env_config["rl"]["training"]["max_nb_steps_per_episode"]
+
+ env_id = textworld.gym.register_game(
+ selected_game,
+ request_infos=request_infos,
+ batch_size=1,
+ asynchronous=False,
+ max_episode_steps=max_steps,
+ wrappers=wrappers
+ )
+
+ self.alfred_env = textworld.gym.make(env_id)
+
+ obs, info = self.alfred_env.reset()
+ self.available_actions = info["admissible_commands"][0]
+ self.instruction_text = obs[0]
+ # Include admissible actions in render cache
+ self.render_cache = self._format_observation(obs[0], self.available_actions)
+ return self.render_cache
+
+ except (RuntimeError, RuntimeWarning) as e:
+ print(f"Error in reset: {e}")
+ next_seed = abs(hash(str(seed))) % (2 ** 32) if seed is not None else None
+ return self.reset(next_seed, mode=self.current_mode)
+
+ def _format_observation(self, obs: str, admissible_actions: list) -> str:
+ """Format observation to include admissible actions."""
+ actions_str = ", ".join(admissible_actions)
+ return f"{obs}\n\nAdmissible actions: [{actions_str}]"
+
+ def step(self, action: str):
+ """
+ Take a step in the environment using the provided action string.
+
+ Reward scheme (matching verl-agent):
+ - reward = config.score * won (10.0 on success, 0.0 otherwise)
+
+ Args:
+ action: The action string to execute
+
+ Returns:
+ observation: Updated observation with admissible actions
+ reward: Sparse reward (score on success, 0 otherwise)
+ done: Whether episode is finished
+ info: Additional information dict
+ """
+ action_is_available = action in self.available_actions
+
+ # Execute action in environment
+ obs, _, dones, infos = self.alfred_env.step([action])
+ observation = obs[0]
+ self.available_actions = infos["admissible_commands"][0]
+ done = dones[0]
+ won = infos["won"][0]
+
+ # Simplified reward matching verl-agent: score * won
+ reward = self.config.score * float(won)
+
+ # Format observation with admissible actions
+ self.render_cache = self._format_observation(observation, self.available_actions)
+
+ info = {
+ "action_is_effective": True,
+ "action_is_valid": action_is_available,
+ "success": won
+ }
+
+ return self.render_cache, reward, done, info
+
+ def render(self):
+ """Return current observation with admissible actions."""
+ return self.render_cache
+
+ def close(self):
+ """Clean up environment resources."""
+ self.render_cache = None
+ if hasattr(self, 'alfred_env') and self.alfred_env is not None:
+ try:
+ self.alfred_env.close()
+ except Exception:
+ pass
+
+
+if __name__ == "__main__":
+ import os
+ os.environ["ALFWORLD_DATA"] = os.path.expanduser("~/.cache/alfworld")
+
+ # Test basic environment functionality
+ print("\n=== Test 1: Basic environment with train mode ===")
+ env = AlfredTXTEnv()
+ obs = env.reset(seed=42, mode='train')
+ print(f"Train observation (first 500 chars):\n{obs[:500]}...")
+
+ # Test mode switching
+ print("\n=== Test 2: Mode switching to val ===")
+ obs = env.reset(seed=42, mode='val')
+ print(f"Val observation (first 500 chars):\n{obs[:500]}...")
+
+ # Test step with admissible action
+ print("\n=== Test 3: Taking a step ===")
+ if env.available_actions:
+ action = env.available_actions[0]
+ print(f"Taking action: {action}")
+ obs, reward, done, info = env.step(action)
+ print(f"Reward: {reward}, Done: {done}, Info: {info}")
+ print(f"New observation (first 300 chars):\n{obs[:300]}...")
+
+ env.close()
+ print("\n=== All tests completed ===")
+
diff --git a/ragen/eval.py b/ragen/eval.py
new file mode 100644
index 0000000000000000000000000000000000000000..c95ba60ef061629acce8c5ed8839f6e833b317c5
--- /dev/null
+++ b/ragen/eval.py
@@ -0,0 +1,47 @@
+
+from ragen.llm_agent.ctx_manager import ContextManager
+from ragen.llm_agent.es_manager import EnvStateManager
+from vllm import LLM, SamplingParams
+from verl.single_controller.ray.base import RayWorkerGroup
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from verl import DataProto
+import hydra
+import os
+from typing import List, Dict
+from verl.protocol import pad_dataproto_to_divisor, unpad_dataproto
+from ragen.llm_agent.base_llm import ConcurrentLLM
+from ragen.llm_agent.agent_proxy import ApiCallingWrapperWg, VllmWrapperWg, LLMAgentProxy, _get_rollout_do_sample
+
+@hydra.main(version_base=None, config_path="../config", config_name="base")
+def main(config):
+ # detect config name from python -m ragen.llm_agent.agent_proxy --config_name frozen_lake
+ os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
+ os.environ["CUDA_VISIBLE_DEVICES"] = str(config.system.CUDA_VISIBLE_DEVICES)
+ tokenizer = AutoTokenizer.from_pretrained(config.actor_rollout_ref.model.path)
+ actor_wg = VllmWrapperWg(config, tokenizer)
+ proxy = LLMAgentProxy(config, actor_wg, tokenizer)
+ import time
+ start_time = time.time()
+ rollouts = proxy.rollout(DataProto(batch=None, non_tensor_batch=None, meta_info={'eos_token_id': 151645, 'pad_token_id': 151643, 'recompute_log_prob': False, 'do_sample': _get_rollout_do_sample(config), 'validate': True}), val=True)
+ end_time = time.time()
+ print(f'rollout time: {end_time - start_time} seconds')
+ # print rollout rewards from the rm_scores
+ rm_scores = rollouts.batch["rm_scores"]
+ metrics = rollouts.meta_info["metrics"]
+ avg_reward = rm_scores.sum(-1).mean().item()
+ print(f'rollout rewards: {avg_reward}')
+ print(f'metrics:')
+ for k, v in metrics.items():
+ print(f'{k}: {v}')
+
+ # save results
+ import time as _time
+ timestamp = _time.strftime("%Y%m%d_%H%M%S")
+ save_dir = os.path.join("results", "eval")
+ os.makedirs(save_dir, exist_ok=True)
+ save_path = os.path.join(save_dir, f"val_rollouts_{timestamp}.pkl")
+ rollouts.save_to_disk(save_path)
+ print(f'save validation results to {save_path}')
+
+if __name__ == "__main__":
+ main()
diff --git a/ragen/eval_api.py b/ragen/eval_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..d0e4b4217f081451b5495b4e800a6c885d90b0e4
--- /dev/null
+++ b/ragen/eval_api.py
@@ -0,0 +1,39 @@
+
+from ragen.llm_agent.ctx_manager import ContextManager
+from ragen.llm_agent.es_manager import EnvStateManager
+from vllm import LLM, SamplingParams
+from verl.single_controller.ray.base import RayWorkerGroup
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from verl import DataProto
+import hydra
+import os
+from typing import List, Dict
+from verl.protocol import pad_dataproto_to_divisor, unpad_dataproto
+from ragen.llm_agent.base_llm import ConcurrentLLM
+from ragen.llm_agent.agent_proxy import ApiCallingWrapperWg, VllmWrapperWg, LLMAgentProxy
+
+@hydra.main(version_base=None, config_path="../config", config_name="evaluate_api_llm")
+def main(config):
+ # detect config name from python -m ragen.llm_agent.agent_proxy --config_name frozen_lake
+ tokenizer = AutoTokenizer.from_pretrained(config.actor_rollout_ref.model.path)
+ actor_wg = ApiCallingWrapperWg(config, tokenizer)
+ proxy = LLMAgentProxy(config, actor_wg, tokenizer)
+ import time
+ start_time = time.time()
+ rollouts = proxy.rollout(DataProto(batch=None, non_tensor_batch=None, meta_info={'eos_token_id': 151645, 'pad_token_id': 151643, 'recompute_log_prob': False, 'do_sample': False, 'validate': True}), val=True)
+ print(f'[DEBUG] rollouts: {rollouts}')
+ end_time = time.time()
+ print(f'rollout time: {end_time - start_time} seconds')
+ # print rollout rewards from the rm_scores
+ rm_scores = rollouts.batch["rm_scores"]
+ metrics = rollouts.meta_info["metrics"]
+ avg_reward = rm_scores.sum(-1).mean().item()
+ print(f'rollout rewards: {avg_reward}')
+ print(f'metrics:')
+ for k, v in metrics.items():
+ print(f'{k}: {v}')
+
+
+
+if __name__ == "__main__":
+ main()
diff --git a/ragen/utils.py b/ragen/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..50b6d0e26440aee66ef0812b639d900a60f26a2b
--- /dev/null
+++ b/ragen/utils.py
@@ -0,0 +1,86 @@
+import random
+import numpy as np
+from contextlib import contextmanager
+from omegaconf import OmegaConf
+import dataclasses
+
+@contextmanager
+def all_seed(seed):
+ random_state = random.getstate()
+ np_random_state = np.random.get_state()
+
+ try:
+ random.seed(seed)
+ np.random.seed(seed)
+ yield
+ finally:
+ random.setstate(random_state)
+ np.random.set_state(np_random_state)
+
+def register_resolvers():
+ try:
+ OmegaConf.register_new_resolver("mul", lambda x, y: x * y)
+ OmegaConf.register_new_resolver("int_div", lambda x, y: int(float(x) / float(y)))
+ OmegaConf.register_new_resolver("not", lambda x: not x)
+ except:
+ pass # already registered
+
+
+
+@dataclasses.dataclass
+class GenerationsLogger:
+
+ def log(self, loggers, samples, step, _type='val'):
+ if 'wandb' in loggers:
+ self.log_generations_to_wandb(samples, step, _type)
+ if 'swanlab' in loggers:
+ self.log_generations_to_swanlab(samples, step, _type)
+
+ def log_generations_to_wandb(self, samples, step, _type='val'):
+ """Log samples to wandb as a table"""
+ import wandb
+
+ # Create column names for all samples
+ columns = ["step"] + sum([[f"input_{i+1}", f"output_{i+1}", f"score_{i+1}"] for i in range(len(samples))], [])
+
+ if not hasattr(self, 'table'):
+ # Initialize the table on first call
+ self.table = wandb.Table(columns=columns)
+
+ # Create a new table with same columns and existing data
+ # Workaround for https://github.com/wandb/wandb/issues/2981#issuecomment-1997445737
+ new_table = wandb.Table(columns=columns, data=self.table.data)
+
+ # Add new row with all data
+ row_data = []
+ row_data.append(step)
+ for sample in samples:
+ row_data.extend(sample)
+
+ new_table.add_data(*row_data)
+
+ # Update reference and log
+ wandb.log({f"{_type}/generations": new_table}, step=step)
+ self.table = new_table
+
+ def log_generations_to_swanlab(self, samples, step, _type='val'):
+ """Log samples to swanlab as text"""
+ import swanlab
+
+ swanlab_text_list = []
+ for i, sample in enumerate(samples):
+ row_text = f"""
+ input: {sample[0]}
+
+ ---
+
+ output: {sample[1]}
+
+ ---
+
+ score: {sample[2]}
+ """
+ swanlab_text_list.append(swanlab.Text(row_text, caption=f"sample {i+1}"))
+
+ # Log to swanlab
+ swanlab.log({f"{_type}/generations": swanlab_text_list}, step=step)