# apply model to validation dataset
predictions = trainer.predict(tokenized_data["validation"])

# Extract the logits and labels from the predictions object
logits = predictions.predictions
labels = predictions.label_ids

# Use your compute_metrics function
metrics = compute_metrics((logits, labels))
print(metrics)

# >> {'Accuracy': 0.889, 'AUC': 0.946}