Exercise

# Evaluating models

Two models have been trained and are available: `large_model`

, which has many parameters; and `small_model`

, which has fewer parameters. Both models have been trained using `train_features`

and `train_labels`

, which are available to you. A separate test set, which consists of `test_features`

and `test_labels`

, is also available.

Your goal is to evaluate relative model performance and also determine whether either model exhibits signs of overfitting. You will do this by evaluating `large_model`

and `small_model`

on both the train and test sets. For each model, you can do this by applying the `.evaluate(x, y)`

method to compute the loss for features `x`

and labels `y`

. You will then compare the four losses generated.

Instructions

**100 XP**

- Evaluate the small model using the train data.
- Evaluate the small model using the test data.
- Evaluate the large model using the train data.
- Evaluate the large model using the test data.