diff --git a/recipe/dapo/README.md b/recipe/dapo/README.md index cbcf48cdc..75b80f1aa 100644 --- a/recipe/dapo/README.md +++ b/recipe/dapo/README.md @@ -36,16 +36,12 @@ bash recipe/dapo/run_dapo_qwen2.5_32b.sh # or other scripts ## Reproduction Runs -| Setup | AIME 2024 Acc. | Hardware | Image | Commit | Enviroment Variables | Training Script | Training Record | +| Setup | AIME 2024 Acc. | Hardware | Image | Commit | Environment Variables | Training Script | Training Record | | -------------------------------------------- | -------------- | --------- | -------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------- | | DAPO | 52% | 16x8xH800 | `hiyouga/verl:ngc-th2.6.0-cu126-vllm0.8.3-flashinfer0.2.2-cxx11abi0` | [`4f80e4`](https://github.com/volcengine/verl/tree/4f80e465c2ec79ab9c3c30ec74b9745de61d0490) | [runtime_env.yaml](https://github.com/volcengine/verl/blob/4f80e465c2ec79ab9c3c30ec74b9745de61d0490/recipe/dapo/runtime_env.yaml) | [run_dapo_qwen2.5_32b.sh](https://github.com/volcengine/verl/blob/4f80e465c2ec79ab9c3c30ec74b9745de61d0490/recipe/dapo/run_dapo_qwen2.5_32b.sh) | [W&B](https://wandb.ai/verl-org/DAPO%20Reproduction%20on%20verl/workspace?nw=wmb4qxfht0n) | | DAPO w/o Dynamic Sampling | 50% | 16x8xH800 | `hiyouga/verl:ngc-th2.6.0-cu126-vllm0.8.3-flashinfer0.2.2-cxx11abi0` | [`4f80e4`](https://github.com/volcengine/verl/tree/4f80e465c2ec79ab9c3c30ec74b9745de61d0490) | [runtime_env.yaml](https://github.com/volcengine/verl/blob/4f80e465c2ec79ab9c3c30ec74b9745de61d0490/recipe/dapo/runtime_env.yaml) | [run_dapo_wo_ds_qwen2.5_32b.sh](https://github.com/volcengine/verl/blob/4f80e465c2ec79ab9c3c30ec74b9745de61d0490/recipe/dapo/run_dapo_wo_ds_qwen2.5_32b.sh) | [W&B](https://wandb.ai/verl-org/DAPO%20Reproduction%20on%20verl/workspace?nw=wmb4qxfht0n) | | DAPO w/o Token-level Loss & Dynamic Sampling | 44% | 16x8xH20 | `hiyouga/verl:ngc-th2.5.1-cu120-vllm0.7.4-hotfix` | [`4f80e4`](https://github.com/volcengine/verl/tree/4f80e465c2ec79ab9c3c30ec74b9745de61d0490) | [runtime_env.yaml](https://github.com/volcengine/verl/blob/4f80e465c2ec79ab9c3c30ec74b9745de61d0490/recipe/dapo/runtime_env.yaml) | [run_dapo_early_qwen2.5_32b.sh](https://github.com/volcengine/verl/blob/4f80e465c2ec79ab9c3c30ec74b9745de61d0490/recipe/dapo/run_dapo_early_qwen2.5_32b.sh) | [W&B](https://wandb.ai/verl-org/DAPO%20Reproduction%20on%20verl/workspace?nw=wmb4qxfht0n) | -> [!NOTE] -> -> Enabling CUDA graph (`enforce_eager=False`) might cause model performance degradation, whose cause is still under investigation. - > [!IMPORTANT] > > **📢 Call for Contribution!** @@ -179,8 +175,18 @@ if self.overlong_buffer_cfg.enable: Most experiments in the paper, including the best-performant one, are run without Overlong Filtering because it's somehow overlapping with Overlong Reward Shaping in terms of properly learning from the longest outputs. So we don't implement it here. +### What's the difference between [the `recipe/dapo` directory in the `main` branch](https://github.com/volcengine/verl/tree/main/recipe/dapo) and the [`recipe/dapo` branch](https://github.com/volcengine/verl/tree/recipe/dapo/recipe/dapo)? + +[The `recipe/dapo` branch](https://github.com/volcengine/verl/tree/recipe/dapo/recipe/dapo) is for **as-is reproduction** and thus won't be updated with new features. + +[The `recipe/dapo` directory in the `main` branch](https://github.com/volcengine/verl/tree/main/recipe/dapo) works as an example of how to extend the latest `verl` to implement an algorithm recipe, which will be maintained with new features. + ### Why can't I produce similar results after modifications? RL infrastructures nowadays still have inherent unrobustness, on which we are still working hard to improve. We strongly recommend to only modify one thing at a time. + +We also list some known problems here: + +1. Enabling CUDA graph (`enforce_eager=False`) might cause model performance degradation, whose cause is still under investigation.