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Evaluate performances on iGSM evaluation dataset

Convert file of model weights

Since vllm loads model from files with Huggingface format (i.e., xxx.safetensor for model and others for tokenizer) while verl only save model with .pt files (e.g., the files model_world_size_2_rank_0.pt in /checkpoints/{project_name}/{run_name}/global_step_100/actor/), we need to first convert it to xxx.safetensor file. To achieve it, you can run

python simple_verl/scripts/evaluation/convert_fsdp_shard_to_safetensor.py --local_dir checkpoints/.../global_step_100/actor

Then it save the files to ./.../actor/huggingface.

Run evaluation with vllm

Then you can evaluate the model on a iGSM test set (we assume it is a .parquet file preprocessed by eval_igsm.py) by

export CUDA_VISIBLE_DEVICES=0
# export VLLM_USE_V1=0 # see below
python scripts/evaluation/eval_igsm --model_dir {path_you_saved_above} [other flags]

where {path_you_saved_above} looks like ./.../actor/huggingface.

Troubleshooting

When using vllm==0.8.1, you may encounter the error

RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method

You can set export VLLM_USE_V1=0 to disable engine V1.