# Evaluation of Absolute Zero Reasoner (AZR) on Math Benchmarks ### Requirements You can install the required packages with the following command: ```bash # Create a new conda environment conda create -n azr_eval python=3.10.16 -y conda activate azr_eval # Install latex2sympy cd evaluation/math_eval tar -xzvf latex2sympy.tar.gz cd eval/latex2sympy pip install -e . cd ../.. # Install other packages. Note the `requirements.txt` doesn't limit packages versions. You can use `freezed_requirements.txt` to install all freezed versions but might include some unused packages. pip install -r requirements.txt # Install flash-attn pip install flash_attn==2.7.4.post1 ``` ### Evaluation First log into huggingface and download the models to be evaluated (if you have not downloaded them yet): ```bash # Download 3B Coder model huggingface-cli download andrewzh/Absolute_Zero_Reasoner-Coder-3b --local-dir-use-symlinks False # Download 7B Coder model huggingface-cli download andrewzh/Absolute_Zero_Reasoner-Coder-7b --local-dir-use-symlinks False # Download 7B Base model huggingface-cli download andrewzh2/Absolute_Zero_Reasoner-Base-7b --local-dir-use-symlinks False # Download 14B Coder model huggingface-cli download andrewzh/Absolute_Zero_Reasoner-Coder-14b --local-dir-use-symlinks False # Download 14B Base model huggingface-cli download andrewzh2/Absolute_Zero_Reasoner-Base-14b --local-dir-use-symlinks False ``` Use the following script to evaluate AZR 7b on 6 benchmark with greedy decoding. There is also a `run.sh` script to evaluate all models on all benchmarks. ```bash bash eval_math_nodes.sh \ --run_name azr_base_7b_seed2 \ --init_model $(ls -d ~/.cache/huggingface/hub/models--andrewzh2--Absolute_Zero_Reasoner-Base-7b/snapshots/*) \ --template azr \ --tp_size 1 \ --add_step_0 true \ --temperature 0 \ --top_p 0.95 \ --max_tokens 16000 \ --benchmarks aime24,aime25,amc23,math500,olympiadbench,minerva_math \ --n_sampling 1 \ --just_wandb false \ --seed 2 ``` **Notes:** - The `--init_model` must be the **absolute path** to your model directory. If you have downloaded them in a different directory, you should change it (be careful wiht "andrewzh" and "andrewzh2" in the path). - You should change `--template` if you are testing other models. It controls the prompt template used for the evaluation. - Full list of benchmarks tested: `aime24,aime25,amc23,math500,olympiadbench,minerva_math`. See dataset under `data/` for other possible benchmarks. - You can change `--benchmarks` to test other benchmarks. ## Acknowledgement The codebase is adapted from [simpleRL-reason](https://github.com/hkust-nlp/simpleRL-reason), which was based on [math-evaluation-harness](https://github.com/ZubinGou/math-evaluation-harness).