def METHOD_NAME(eval_preds):
    labels = paddle.to_tensor(eval_preds.label_ids, dtype="int64")
    preds = paddle.to_tensor(eval_preds.predictions)
    preds = paddle.nn.functional.sigmoid(preds)
    preds = preds[labels != -100].numpy()
    labels = labels[labels != -100].numpy()
    preds = preds > data_args.threshold
    micro_f1 = f1_score(y_pred=preds, y_true=labels, average="micro")
    macro_f1 = f1_score(y_pred=preds, y_true=labels, average="macro")
    return {"micro_f1": micro_f1, "macro_f1": macro_f1}