NLP：如何使用 GoldParse 对象训练 spaCy NER 模型

如何解决NLP：如何使用 GoldParse 对象训练 spaCy NER 模型

我正在尝试使用 GoldParse 对象训练 spaCy NER 模型。这就是我所做的：

向 NER 模型添加额外标签

$ python3 test.py
-----BEGIN RSA PRIVATE KEY-----
MIIDCgIBAAKBpwYMzwEMAwLajdq74D0Q7NRXICJr/EZHI6z0NcmVbiAj139f7apO
WG0KV9MJVjENFkh1Ld64B2GY8Ibq7/jCz/nPU67eQPmAKU59COzGK0+WSiDJ+twE
LwH0eqzvC6DauDngw2biWIR6p/A9OHFXm2xANW1CPq64a/h9IFlXslOhHtwjfv8k
N0mZ/PHK9vxWJlWwxEmI/sBXJlAa1fxxCl62H2N4YIvrAgMBAAECgacCOSrJY7Sn
k9GVlH1vc4zU67+vZqeq2/HMWWJ61iNGRGWpNYONloUAbVChCUlXdUu/DPDybAaq
Yx3hNu1BKbZsQziphpuyFNsZMPHasWixMrXDHvTWUcEuOYKjk4EksDsCplo1BryY
+O6kel711Xi6zVXEt/1aWc8s6KP1sIPunSbUh4m9BIPQzrQ6ImdgY0XtSqpIvw2I
2zPFnRb2ZsMx7KgnXt1VlzX2g=
-----END RSA PRIVATE KEY-----

Here is your private key :
-----BEGIN RSA PRIVATE KEY-----
MIIDCgIBAAKBpwYMzwEMAwLajdq74D0Q7NRXICJr/EZHI6z0NcmVbiAj139f7apO
WG0KV9MJVjENFkh1Ld64B2GY8Ibq7/jCz/nPU67eQPmAKU59COzGK0+WSiDJ+twE
LwH0eqzvC6DauDngw2biWIR6p/A9OHFXm2xANW1CPq64a/h9IFlXslOhHtwjfv8k
N0mZ/PHK9vxWJlWwxEmI/sBXJlAa1fxxCl62H2N4YIvrAgMBAAECgacCOSrJY7Sn
k9GVlH1vc4zU67+vZqeq2/HMWWJ61iNGRGWpNYONloUAbVChCUlXdUu/DPDybAaq
Yx3hNu1BKbZsQziphpuyFNsZMPHasWixMrXDHvTWUcEuOYKjk4EksDsCplo1BryY
+O6kel711Xi6zVXEt/1aWc8s6KP1sIPunSbUh4m9BIPQzrQ6ImdgY0XtSqpIvw2I
2zPFnRb2ZsMx7KgnXt1VlzX2g=
-----END RSA PRIVATE KEY-----

训练 NER 模型

add_ents = ['A1','B1','C1','D1','E1','F1','G1'] # sample labels

# Create a pipe if it does not exist
if "ner" not in nlp.pipe_names:
    ner = nlp.create_pipe("ner") 
    nlp.add_pipe(ner)
else:
    ner = nlp.get_pipe("ner")

for e in add_ents:
    ner.add_label(e)

这里 X 是 Doc 对象的列表，y 是对应的 GoldParse 对象的列表。执行时我遇到以下错误：

other_pipes = [pipe for pipe in nlp.pipe_names if pipe != "ner"]
model = None # Since we training a fresh model not a saved model
with nlp.disable_pipes(*other_pipes):  # only train ner
    if model is None:
        optimizer = nlp.begin_training()
    else:
        optimizer = nlp.resume_training()
    for i in range(20):
        loss = {}
        nlp.update(X,y,sgd=optimizer,drop=0.0,losses=loss)
        print("Loss: ",loss)

我尝试搜索解决方案，但找不到任何相关内容。有没有办法解决这个问题？