尝试训练spacy模型时的值错误

Question

我尝试训练一个spacy模型，但最近我开始出现一些错误，我出现了以下错误，我希望有人能帮助我解决错误

def train_model(model, train_data, optimizer, batch_size, epochs=10):
losses = {}
random.seed(1)

for epoch in range(epochs):
random.shuffle(train_data)

batches = minibatch(train_data, size=batch_size)
for batch in batches:
# Split batch into texts and labels
texts, labels = zip(*batch)

# Update model with texts and labels
nlp.update(texts, labels, sgd=optimizer, losses=losses)
print("Loss: {}".format(losses['textcat']))

return losses['textcat']


optimizer = nlp.begin_training()
batch_size = 5
epochs = 20

# Training the model
train_model(nlp, train_data, optimizer, batch_size, epochs)

以下是显示存在值错误的错误

ValueError                                                       
Traceback (most recent call last)
~AppDataLocalTemp/ipykernel_16120/3494358196.py in <module>
4 
5 # Training the model
----> 6 train_model(nlp, train_data, optimizer, batch_size, epochs)
~AppDataLocalTemp/ipykernel_16120/3158014372.py in train_model(model, train_data, optimizer, batch_size, epochs)
12 
13             # Update model with texts and labels
---> 14             nlp.update(texts, labels, sgd=optimizer, losses=losses)
15         print("Loss: {}".format(losses['textcat']))
16 
~anaconda3libsite-packagesspacylanguage.py in update(self, examples, _, drop, sgd, losses, component_cfg, exclude, annotates)
1132         """
1133         if _ is not None:
-> 1134             raise ValueError(Errors.E989)
1135         if losses is None:
1136             losses = {}
ValueError: [E989] `nlp.update()` was called with two positional arguments. This may be due to a backwards-incompatible change to the format of the training data in spaCy 3.0 onwards. The 'update' function should now be called with a batch of Example objects, instead of `(text, annotation)` tuples. 

Answer 1

根据文档，他们在版本3.x中进行了一些更改，现在它直接使用batch，而不拆分texts, labels = zip(*batch)。

for batch in batches:
nlp.update(batch, sgd=optimizer, losses=losses)

仅此而已。