Dataset
Also: datasets, training data
A collection of examples used to train or test a model.
The fuller definition
A dataset is an organized collection of examples used for tasks such as training, testing, or analysis. Its contents and selection determine what conclusions it can support.
- ExamplesInputs paired with the expected output.
- PredictionThe model produces an output.
- LossHow far off it was, as a number.
- UpdateParameters nudged to reduce the loss; repeat.
Training ends at the knowledge cutoff. Whatever the examples contained, including their gaps and biases, is what the model learned.
A concrete example
A labelled set of fictional emails is used to test whether a model distinguishes proposals from agreements.
The distinction that matters
A large dataset can still be unrepresentative, duplicated, or incorrectly labelled.
Related terms
Training
Adjusting a model with examples and a learning rule. The aim is to improve how it handles tasks.
Training & generationTest set
Examples held back from training so you can check how the model does on things it has not seen.
Reliability & securityData leakage
Data reaching a place it should not. In model tests, it can also mean test answers have reached the training data.
Where it is taught
How models learn from examplesSource and further reading
Hugging Face · LLM courseThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.