For this task, load the accuracy metric (see the 🤗 Evaluate quick tour to learn more about how to load and compute a metric):

import evaluate
accuracy = evaluate.load("accuracy")

Then create a function that passes your predictions and labels to [~evaluate.EvaluationModule.compute] to calculate the accuracy:

import numpy as np
def compute_metrics(eval_pred):
     predictions, labels = eval_pred
     predictions = np.argmax(predictions, axis=1)
     return accuracy.compute(predictions=predictions, references=labels)

Your compute_metrics function is ready to go now, and you'll return to it when you setup your training.