Datasets:
Question
stringlengths 2
3
| Design
stringclasses 4
values | Criterion
stringclasses 4
values |
---|---|---|
Q1 | Kitchen Utensil Grip | Lightweight |
Q2 | Kitchen Utensil Grip | Resistant to Heat |
Q3 | Kitchen Utensil Grip | Corrosion Resistant |
Q4 | Kitchen Utensil Grip | High Strength |
Q5 | Spacecraft Component | Lightweight |
Q6 | Spacecraft Component | Resistant to Heat |
Q7 | Spacecraft Component | Corrosion Resistant |
Q8 | Spacecraft Component | High Strength |
Q9 | Underwater Component | Lightweight |
Q10 | Underwater Component | Resistant to Heat |
Q11 | Underwater Component | Corrosion Resistant |
Q12 | Underwater Component | High Strength |
Q13 | Safety Helmet | Lightweight |
Q14 | Safety Helmet | Resistant to Heat |
Q15 | Safety Helmet | Corrosion Resistant |
Q16 | Safety Helmet | High Strength |
MSEval Dataset:
A benchmark designed to facilitate evaluation and modify the behavior of a foundation model through different existing techniques in the context of material selection for conceptual design.
The data is collected by conducting a survey of experts in the field of material selection. The same questions mentioned in keyquestions.csv are asked to experts.
This can be used to evaluate a Language model performance and its spread compared to a human evaluation.
Overview
We introduce MSEval, a benchmark derived from survey results of experts in the field of material selection.
The MixEval consists of two files: CleanResponses
and AllResponses
. Below presents the dataset file tree:
MSEval
│
├── AllResponses.csv
└── CleanResponses.csv
└── KeyQuestions.csv
Dataset Usage
An example use of the dataset using the datasets library is shown in https://github.com/cmudrc/MSEval
To use this dataset using pandas:
import pandas as pd
df = pd.read_csv("hf://datasets/cmudrc/Material_Selection_Eval/AllResponses.csv")
Replace AllResponses with CleanResponses and KeyQuestions in the pathname if required.
license: mit
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