Model selection for tasks in NLP - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is model selection in machine learning?

Model selection is the process of choosing the best machine learning model for a specific task based on performance and suitability.

beginner

Why is it important to select the right model for a task?

Choosing the right model ensures better accuracy, faster training, and efficient use of resources for the task at hand.

intermediate

Name two common criteria used to select models for NLP tasks.

Common criteria include accuracy (or other performance metrics) and computational efficiency (speed and resource use).

intermediate

How does the size of the dataset influence model selection?

Smaller datasets often require simpler models to avoid overfitting, while larger datasets can support more complex models.

intermediate

What role does the task type (e.g., classification, generation) play in model selection?

The task type determines which model architectures are suitable, such as classification models for labeling tasks and sequence-to-sequence models for generation.

Which factor is NOT typically considered in model selection?

A Model accuracy

B Model color

C Training time

D Dataset size

Model color is irrelevant; accuracy, training time, and dataset size are important factors.

For a small dataset, which model is usually better?

A A very deep neural network

B A model trained on unrelated data

C A model with many parameters

D A simple model

Simple models reduce overfitting risk on small datasets.

Which model type is best for text generation tasks?

A Sequence-to-sequence models

B Linear regression

C Decision trees

D Clustering algorithms

Sequence-to-sequence models handle input-output sequences well, ideal for generation.

What metric is commonly used to evaluate classification models?

A BLEU score

B Mean squared error

C Accuracy

D Perplexity

Accuracy measures correct predictions in classification tasks.

Why might computational efficiency matter in model selection?

A To reduce training and prediction time

B To make the model colorful

C To increase model complexity unnecessarily

D To ignore dataset size

Efficient models save time and resources during training and use.

Explain how dataset size affects your choice of model for an NLP task.

Think about how much data you have and how complex your model should be.

Describe why task type is important when selecting a model in NLP.

Consider what the model needs to do with the text.