overfitted

the model was severely overfitted to the training data.

we need to avoid being overfitted during the training process.

the data scientist suspected the neural network was overfitted.

regularization techniques can help prevent overfitting.

the validation set revealed the model was overfitted.

an overfitted model performs poorly on unseen data.

we’re trying to reduce overfitting with dropout layers.

the algorithm became overfitted after too many epochs.

cross-validation helps identify an overfitted model.

the goal is to find a balance and avoid being overfitted.

it's crucial to check for overfitting during model development.