datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
student-grades-demo
Student Grades Demo Dataset
This dataset contains student grades data with both true labels and noisy (corrupted) labels.
Dataset Description
The dataset includes:
Student exam scores (exam_1, exam_2, exam_3)
Notes field
True letter grades (letter_grade)
Noisy/corrupted letter grades (noisy_letter_grade)
This is useful for demonstrating and validating label error detection methods.
Usage
import pandas as pd
# Load the dataset
df =… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/student-grades-demo.bad_data_gsm8k_svamp.csvSome bad data discovered in the popular GSM8K and SVAMP LLM benchmarking datasets.
These examples have incorrect answers in the corresponding math problem benchmark dataset, and should not be used to evaluate AI models.
We detected this bad data automatically using Cleanlab's Trustworthy Language Model. TLM's estimated trustworthiness score for each example is also provided.
Example error found in the GSM8K dataset:
Question: After scoring 14 points, Erin now has three times… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/bad_data_gsm8k_svamp.csv.student-grades
Student Grades Dataset
Dataset Description
This dataset contains student grade data used in the cleanlab tutorial: Improving ML Performance via Data Curation with Train vs Test Splits.
The task is to predict each student's final letter grade (A, B, C, D, F) based on their exam scores and notes.
Dataset Summary
Total Examples: ~750 (train + test)
Task: Multi-class classification
Features:
exam_1: Score on first exam (0-100)
exam_2: Score on second exam (0-100)… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/student-grades.databricks-dolly-15k-cleanset
Summary
databricks-dolly-15k-cleanset can be used to produced CLEANed up versions of the popular databricks-dolly-15k dataSET, which was used to fine-tune the Dolly 2.0. The original databricks-dolly-15k contains 15,000 human-annotated instruction-response pairs covering various categories. However, there are many low-quality responses, incomplete/vague prompts, and other problematic text lurking in the dataset (as with for all real-world instruction tuning datasets). We ran… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/databricks-dolly-15k-cleanset.student-grades-regression
Student Grades Regression Dataset
This dataset contains student grades data for regression tasks. It is designed for demonstrating regression techniques and data quality methods.
Dataset Description
The dataset includes:
train.csv - Training data with student features and grade labels
test.csv - Test data for evaluation
This is a regression version of the student grades dataset, where the target variable is continuous.
Usage
import pandas as pd
# Load the… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/student-grades-regression.grades-tabular-demo
Grades Tabular Demo Dataset
This dataset contains student grades data for tabular classification tasks.
Dataset Description
A tabular dataset containing student information and their grades, useful for demonstrating data quality techniques on tabular data.
Usage
import pandas as pd
# Load the dataset
df = pd.read_csv("hf://datasets/Cleanlab/grades-tabular-demo/grades-tabular-demo.csv")
print(df.head())
License
MIT License
grades-tabular-demo-with-outliers
Grades Tabular Demo with Outliers Dataset
This dataset contains student grades data for tabular classification tasks, including some outliers to demonstrate data quality techniques.
Dataset Description
A tabular dataset containing student information and their grades, useful for demonstrating data quality techniques on tabular data.
Usage
import pandas as pd
# Load the dataset
df =… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/grades-tabular-demo-with-outliers.