4.3 KiB
4.3 KiB
| 1 | section | parameter | value | source |
|---|---|---|---|---|
| 2 | Run identity | Base model | Qwen/Qwen3-4B | queue/script override |
| 3 | Run identity | Dataset | Physics / SciKnowEval physics | run_qwen3_generalization.sh |
| 4 | Run identity | Method | GRPO | run_qwen3_generalization.sh |
| 5 | Run identity | Config | baseline_grpo | run_qwen3_generalization.sh |
| 6 | Run identity | Experiment | qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8 | run_qwen3_generalization.sh |
| 7 | Run identity | W&B run | run-20260702_073403-o8ivivjg | wandb |
| 8 | Data | Train file | datasets/sciknoweval/physics/train.parquet | script override |
| 9 | Data | Validation file | datasets/sciknoweval/physics/test.parquet | script override |
| 10 | Data | Train batch size | 32 | queue/script override |
| 11 | Data | Train max samples | 3200 | queue/script override |
| 12 | Data | Prompt key | prompt | legacy_data.yaml default |
| 13 | Data | Reward key | data_source | legacy_data.yaml default |
| 14 | Data | Shuffle train data | True | user.yaml / legacy_data.yaml |
| 15 | Data | Validation shuffle | False | legacy_data.yaml default |
| 16 | Data | Filter overlong prompts | True | user.yaml |
| 17 | Data | Prompt truncation | error | legacy_data.yaml default |
| 18 | Data | enable_thinking | false | script override |
| 19 | Schedule | Total training steps | 100 | queue/script override |
| 20 | Schedule | Total epochs | 30 | ppo_trainer/user.yaml default |
| 21 | Schedule | Validation before train | False | queue/script override |
| 22 | Schedule | Save frequency | 10 | queue/script override |
| 23 | Schedule | Validation frequency | 10 | queue/script override |
| 24 | Sequence | Max prompt length | 2048 | queue/script override |
| 25 | Sequence | Max response length | 8192 | queue/script override |
| 26 | Sequence | Max model length | 10240 | queue/script override |
| 27 | Sequence | Actor max token length per GPU | 10240 | queue/script override |
| 28 | Rollout | Rollout engine | vllm | user.yaml |
| 29 | Rollout | Rollout dtype | bfloat16 | rollout.yaml default |
| 30 | Rollout | Train rollout n | 8 | queue/script override |
| 31 | Rollout | Train rollout temperature | 1.0 | script override |
| 32 | Rollout | Train rollout top_p | 1.0 | script override |
| 33 | Rollout | Train rollout do_sample | True | rollout.yaml default |
| 34 | Rollout | Calculate rollout log probs | True | baseline_grpo.yaml / script override |
| 35 | Rollout | Max num batched tokens | 10240 | queue/script override |
| 36 | Rollout | vLLM GPU memory utilization | 0.8 | queue/script override |
| 37 | Rollout | Tensor model parallel size | 2 | rollout.yaml default |
| 38 | Rollout | Free cache engine | True | rollout.yaml default |
| 39 | Validation | Validation rollout n | 16 | queue/script override |
| 40 | Validation | Validation temperature | 0.6 | queue/script override |
| 41 | Validation | Validation top_p | 0.95 | queue/script override |
| 42 | Validation | Validation do_sample | True | queue/script override |
| 43 | Optimization | Optimizer | AdamW | fsdp optimizer config |
| 44 | Optimization | Learning rate | 1e-6 | GRPO method override |
| 45 | Optimization | LR scheduler | constant | W&B config |
| 46 | Optimization | LR warmup steps | 10 | script override |
| 47 | Optimization | Weight decay | 0.01 | script override |
| 48 | Optimization | Betas | (0.9, 0.999) | W&B config |
| 49 | Optimization | Gradient clip | 1.0 | script override |
| 50 | PPO/GRPO | Policy loss mode | vanilla | method override |
| 51 | PPO/GRPO | Advantage estimator | grpo | baseline_grpo.yaml |
| 52 | PPO/GRPO | Normalize GRPO advantages by std | False | baseline_grpo.yaml / script override |
| 53 | PPO/GRPO | PPO epochs | 1 | W&B config |
| 54 | PPO/GRPO | PPO mini batch size | 8 | queue/script override |
| 55 | PPO/GRPO | PPO micro batch size per GPU | 1 | user.yaml |
| 56 | PPO/GRPO | Clip ratio low | 0.2 | script override |
| 57 | PPO/GRPO | Clip ratio high | 0.28 | script override |
| 58 | PPO/GRPO | Gamma | 1.0 | ppo_trainer.yaml default |
| 59 | PPO/GRPO | Lambda | 1.0 | ppo_trainer.yaml default |
| 60 | PPO/GRPO | Actor KL loss coef | 0.0 | method override |
| 61 | PPO/GRPO | Use KL in reward | False | ppo_trainer/user.yaml |
| 62 | Rollout correction | Importance sampling mode | token | script override |
| 63 | Rollout correction | IS threshold | 2.0 | script override |
| 64 | FSDP/System | Actor strategy | fsdp | dp_actor.yaml |
| 65 | FSDP/System | FSDP dtype | bfloat16 | W&B config |
| 66 | FSDP/System | FSDP model dtype | fp32 | W&B config |
| 67 | FSDP/System | Use torch compile | True | W&B config |
| 68 | FSDP/System | GPUs per node | 8 | queue/script override |
| 69 | FSDP/System | Nodes | 1 | user.yaml |
| 70 | FSDP/System | GPU type | NVIDIA H200 | wandb-metadata |
| 71 | Checkpoint/Logging | Checkpoint root | checkpoints/datasets/sciknoweval/physics | script override |
| 72 | Checkpoint/Logging | Latest checkpointed iteration | 100 | latest_checkpointed_iteration.txt |
| 73 | Checkpoint/Logging | Max actor checkpoints to keep | 1 | user.yaml |
| 74 | Checkpoint/Logging | Logger | console, wandb | ppo_trainer.yaml |
| 75 | Checkpoint/Logging | W&B entity | seongryongjung-chung-ang-university | environment |
| 76 | Checkpoint/Logging | W&B project | SDPO-root | user.yaml project_name |
| 77 | Checkpoint/Logging | W&B group | QWEN3-GRPO-generalization | method override |