请提出你的问题

使用ERNIE模型，进行微调时，出现错误：
Traceback (most recent call last):
File "D:\1.地下空间数据获取\netBuild\ERNIE\train.py", line 95, in
logits = model(input_ids, token_type_ids)
File "D:\app\python38\lib\site-packages\paddle\nn\layer\layers.py", line 1429, in call
return self.forward(*inputs, **kwargs)
File "D:\app\python38\lib\site-packages\paddlenlp\transformers\ernie\modeling.py", line 709, in forward
outputs = self.ernie(
File "D:\app\python38\lib\site-packages\paddle\nn\layer\layers.py", line 1429, in call
return self.forward(*inputs, **kwargs)
File "D:\app\python38\lib\site-packages\paddlenlp\transformers\ernie\modeling.py", line 357, in forward
encoder_outputs = self.encoder(
File "D:\app\python38\lib\site-packages\paddle\nn\layer\layers.py", line 1429, in call
return self.forward(*inputs, **kwargs)
File "D:\app\python38\lib\site-packages\paddlenlp\transformers\model_outputs.py", line 304, in _transformer_encoder_fwd
layer_outputs = mod(
File "D:\app\python38\lib\site-packages\paddle\nn\layer\layers.py", line 1429, in call
return self.forward(*inputs, **kwargs)
File "D:\app\python38\lib\site-packages\paddlenlp\transformers\model_outputs.py", line 83, in _transformer_encoder_layer_fwd
attn_outputs = self.self_attn(src, src, src, src_mask, cache)
File "D:\app\python38\lib\site-packages\paddle\nn\layer\layers.py", line 1429, in call
return self.forward(*inputs, **kwargs)
File "D:\app\python38\lib\site-packages\paddle\nn\layer\transformer.py", line 432, in forward
out = tensor.matmul(weights, v)
File "D:\app\python38\lib\site-packages\paddle\tensor\linalg.py", line 239, in matmul
return _C_ops.matmul(x, y, transpose_x, transpose_y)
ValueError: (InvalidArgument) Pointer C should not be null.
[Hint: C should not be null.] (at ..\paddle/phi/kernels/funcs/blas/blas_impl.h:1373)

微调代码为：
model = ErnieForTokenClassification.from_pretrained("ernie-1.0", num_classes=len(labelVocab))
step = 0
for epoch in range(50):
for idx, (input_ids, token_type_ids, length, labels) in enumerate(train_loader):
logits = model(input_ids, token_type_ids)
loss = paddle.mean(loss_fn(logits, labels))
loss.backward()
optimizer.step()
optimizer.clear_grad()
step += 1
print("epoch:%d - step:%d - loss: %f" % (epoch, step, loss))
evaluate(model, metric, dev_loader)

我之前用一套训练数据运行成功了，换了一套训练数据就报错了，昨天觉得是数据本身或者预处理不当导致出现问题，但今天是在预训练到第三轮才报的错，应该不是数据本身或者预处理的问题。没有什么解决思路，希望能给与解答，谢谢。