# GSM8K [GSM8K](https://arxiv.org/pdf/2110.14168) is a dataset consisting of diverse grade school math word problems. Contributed by [@jjallaire](https://github.com/jjallaire) ## Usage ### Installation There are two ways of using Inspect Evals, from pypi as a dependency of your own project and as a standalone checked out GitHub repository. If you are using it from pypi, install the package and its dependencies via: ```bash pip install inspect-evals ``` If you are using Inspect Evals in its repository, start by installing the necessary dependencies with: ```bash uv sync ``` ### Running evaluations Now you can start evaluating models. For simplicity's sake, this section assumes you are using Inspect Evals from the standalone repo. If that's not the case and you are not using `uv` to manage dependencies in your own project, you can use the same commands with `uv run` dropped. ```bash uv run inspect eval inspect_evals/gsm8k --model openai/gpt-5-nano ``` You can also import tasks as normal Python objects and run them from python: ```python from inspect_ai import eval from inspect_evals.gsm8k import gsm8k eval(gsm8k) ``` After running evaluations, you can view their logs using the `inspect view` command: ```bash uv run inspect view ``` For VS Code, you can also download [Inspect AI extension for viewing logs](https://inspect.ai-safety-institute.org.uk/log-viewer.html). If you don't want to specify the `--model` each time you run an evaluation, create a `.env` configuration file in your working directory that defines the `INSPECT_EVAL_MODEL` environment variable along with your API key. For example: ```bash INSPECT_EVAL_MODEL=anthropic/claude-opus-4-1-20250805 ANTHROPIC_API_KEY= ``` ## Options You can control a variety of options from the command line. For example: ```bash uv run inspect eval inspect_evals/gsm8k --limit 10 uv run inspect eval inspect_evals/gsm8k --max-connections 10 uv run inspect eval inspect_evals/gsm8k --temperature 0.5 ``` See `uv run inspect eval --help` for all available options. ## Parameters ### `gsm8k` - `fewshot` (int): The number of few shots to include (default: `10`) - `fewshot_seed` (int): The seed for generating few shots (default: `42`) - `shuffle_fewshot` (bool): Whether we take the first N samples of the dataset as the fewshot examples, or randomly sample to get the examples. (default: `True`) ## Dataset Here is an example prompt from the dataset (after it has been further processed by Inspect): >Solve the following math problem step by step. The last line of your response should be of the form "ANSWER: $ANSWER" (without quotes) where $ANSWER is the answer to the problem. > >Janet’s ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market? > >Remember to put your answer on its own line at the end in the form "ANSWER: $ANSWER" (without quotes) where $ANSWER is the answer to the problem, and you do not need to use a \\boxed command. > >Reasoning: The model is then expected to generate reasoning steps and provide a final answer. ## Scoring An accuracy is calculated over the datapoints. The correctness is based on an exact-match criterion and whether the model's final answer is correct. ## Changelog ### [2-A] - 2026-02-16 - Migrate version to new scheme. See [#907](https://github.com/UKGovernmentBEIS/inspect_evals/pull/907). ### [1.0.1] - 2025-12-18 - Adds backoff policy for functions that connect to huggingface servers.