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Eval for Mathematical Functions
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Eval details 📑
Eval name
Arithmetic Function
Eval description
Evaluate for wrong calculation & evaluation result
What makes this a useful eval?
I believe this eval is worth including because it is factually wrong, and I've tested both for GPT-3.5 & GPT-4 in ChatGPT that it yields wrong result.

Criteria for a good eval ✅
Below are some of the criteria we look for in a good eval. In general, we are seeking cases where the model does not do a good job despite being capable of generating a good response (note that there are some things large language models cannot do, so those would not make good evals).
Your eval should be:
- [x] Thematically consistent: The eval should be thematically consistent. We'd like to see a number of prompts all demonstrating some particular failure mode. For example, we can create an eval on cases where the model fails to reason about the physical world.
- [x] Contains failures where a human can do the task, but either GPT-4 or GPT-3.5-Turbo could not.
- [x] Includes good signal around what is the right behavior. This means either a correct answer for
Basicevals or theFactModel-graded eval, or an exhaustive rubric for evaluating answers for theCriteriaModel-graded eval. - [ ] Include at least 100 high quality examples
If there is anything else that makes your eval worth including, please document it below.
Unique eval value
Insert what makes your eval high quality that was not mentioned above. (Not required)
Eval structure 🏗️
Your eval should
- [x] Check that your data is in
evals/registry/data/{name} - [x] Check that your yaml is registered at
evals/registry/evals/{name}.jsonl - [x] Ensure you have the right to use the data you submit via this eval
(For now, we will only be approving evals that use one of the existing eval classes. You may still write custom eval classes for your own cases, and we may consider merging them in the future.)
Final checklist 👀
Submission agreement
By contributing to Evals, you are agreeing to make your evaluation logic and data under the same MIT license as this repository. You must have adequate rights to upload any data used in an Eval. OpenAI reserves the right to use this data in future service improvements to our product. Contributions to OpenAI Evals will be subject to our usual Usage Policies (https://platform.openai.com/docs/usage-policies).
- [x] I agree that my submission will be made available under an MIT license and complies with OpenAI's usage policies.
Email address validation
If your submission is accepted, we will be granting GPT-4 access to a limited number of contributors. Access will be given to the email address associated with the merged pull request.
- [x] I acknowledge that GPT-4 access will only be granted, if applicable, to the email address used for my merged pull request.
Limited availability acknowledgement
We know that you might be excited to contribute to OpenAI's mission, help improve our models, and gain access to GPT-4. However, due to the requirements mentioned above and high volume of submissions, we will not be able to accept all submissions and thus not grant everyone who opens a PR GPT-4 access. We know this is disappointing, but we hope to set the right expectation before you open this PR.
- [x] I understand that opening a PR, even if it meets the requirements above, does not guarantee the PR will be merged nor GPT-4 access granted.
Submit eval
- [ ] I have filled out all required fields in the evals PR form
- [x] (Ignore if not submitting code) I have run
pip install pre-commit; pre-commit installand have verified thatblack,isort, andautoflakeare running when I commit and push
Failure to fill out all required fields will result in the PR being closed.
Eval JSON data
Since we are using Git LFS, we are asking eval submitters to add in their first 100 JSONL eval lines.
View evals in JSON
Eval
{"input":[{"role":"system","content":"F(x) = 3 * 3x, M(x) = 2 * F(x), evaluate M(10), carefully step-by-step, show your reasoning"}],"ideal":"To evaluate M(10), we first need to find the value of F(10), since M(x) is dependent on F(x). Let's carefully go step by step.\n\nEvaluate F(10):\nF(x) = 3 * 3(10)\nF(10) = 3 * 3(10)\nNow, we need to compute the value of 3(10):\n3(10) = 30\n\nSo, F(10) = 3 * 30 = 90\n\nEvaluate M(10):\nM(x) = 2 * F(x)\nM(10) = 2 * F(10) = 2 * 90 = 180\nTherefore, M(10) = 180."}
{"input":[{"role":"system","content":"F(x) = 3 * 2x, M(x) = 2 * F(x), evaluate M(4), carefully step-by-step, show your reasoning"}],"ideal":"Let's evaluate M(4) step-by-step:\n\nFirst, we need to find F(x). We are given the function F(x) = 3 * 2x.\n\nNext, we need to find F(4) by substituting x = 4 into the function F(x):\nF(4) = 3 * 2(4)\n\nNow, let's evaluate 2(4):\n2(4) = 8\n\nThen, substitute the value of 2(4) back into F(4):\nF(4) = 3 * 8\n\nNow, evaluate F(4):\nF(4) = 24\n\nNow that we have the value of F(4), we can find M(x) using the given function M(x) = 2 * F(x).\n\nSubstitute the value of F(4) into M(x):\nM(4) = 2 * F(4)\nM(4) = 2 * 24\n\nFinally, evaluate M(4):\nM(4) = 48\n\nSo, M(4) = 48."}
{"input":[{"role":"system","content":"F(x) = 4 * 5x, M(x) = 2 * F(x), evaluate M(2), carefully step-by-step, show your reasoning"}],"ideal":"Let's carefully evaluate M(2) step-by-step.\n\nFirst, we are given two functions:\n\nF(x) = 4 * 5x\nM(x) = 2 * F(x)\nOur goal is to evaluate M(2), so we'll first need to find F(2) and then substitute that result into M(x).\n\nStep 1: Evaluate F(2)\nF(x) = 4 * 5x\nF(2) = 4 * 5(2)\n\n5^2 = 25, so:\nF(2) = 4 * 10\nF(2) = 40\n\nNow that we have found F(2), we can substitute this value into M(x).\n\nStep 2: Evaluate M(2)\nM(x) = 2 * F(x)\nM(2) = 2 * F(2)\nM(2) = 2 * 40 (since F(2) = 40)\n\nFinally, we multiply to get the result:\nM(2) = 80\n\nSo, M(2) = 80."}
Haven't added more samples, gonna add if maintainers OK to move forward
Closing the PR due to inactivity; please feel free to reopen if you get a chance to address comments.