如何在spaCy中只训练特定的实体标签？

import spacy

nlp = spacy.blank("en")

nlp.add_label("YOUR_LABEL")

disable_pipes = [pipe for pipe in nlp.pipe_names if pipe != "ner"]
with nlp.disable_pipes(*disable_pipes):
    # 在这里进行训练

TRAIN_DATA = [
    ("Some text with YOUR_LABEL", {"entities": [(10, 20, "YOUR_LABEL")]}),
    # 添加更多的训练数据
]

import random
from spacy.util import minibatch, compounding

# 设置随机种子
random.seed(0)

# 初始化模型
nlp.begin_training()

# 设置训练循环的次数
n_iter = 10

# 循环训练
for i in range(n_iter):
    # 打乱训练数据
    random.shuffle(TRAIN_DATA)
    losses = {}
    
    # 使用minibatch进行训练
    batches = minibatch(TRAIN_DATA, size=compounding(4.0, 32.0, 1.001))
    for batch in batches:
        texts, annotations = zip(*batch)
        nlp.update(texts, annotations, losses=losses)
    
    # 打印训练损失
    print("Losses", losses)