You need to return a dictionary with the metrics you want (please checkout the course on the Trainer
and the Trainer video) so in this case:
def compute_metrics(eval_pred):
metric1 = load_metric("precision")
metric2 = load_metric("recall")
logits, labels = eval_pred
predictions = np.argmax(logits, axis=-1)
precision = metric1.compute(predictions=predictions, references=labels)["precision"]
recall = metric2.compute(predictions=predictions, references=labels)["recall"]
return {"precision": precision, "recall": recall}