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ccks金融事件主体抽取
您好,非常感谢你的分享,我最近在学习这方面的东西,这个项目无论是思路还是代码都给了我很大帮助,我打算复现你的项目。
在复现mutil_pointer 部分的时候发现缺少你在README.md中提到的文件 "结果融合:python ensemble.py
"。希望可以补充这个文件。
另外,我在执行 python train.py
的过程中发现,会报错TypeError: forward() got an unexpected keyword argument 'output_all_encoded_layers'
, 需将 model_NEZHA.py
文件中 类NEZHAModel
中的 output_hidden_states
修改为output_all_encoded_layers
。
你好:
经过preprocess.py处理后的训练集数据train.data,不包含负样本。请问,您是对负样本如何处理的?不把负样本添加到训练集中吗?
博主你好!
我在复现你的代码时,出现一些问题。
我将其修改为一样的size后,发现跑出来的结果不太对。
其中一个错误是model部分的133行。
outputs = self.bert(
input_ids,
attention_mask=attention_mask,
token_type_ids=token_type_ids,
output_all_encoded_layers=True
) # sequence_output, pooled_output, (hidden_states), (attentions)
output_all_encoded_layers并没有被定义。
我将其 注释掉后,又出现其他问题,后面全部修改完,结果不太对。最后发现还是这个地方出了问题。由于中间代码连接有点复杂,可否加个联系方式,请教一下。
我的QQ号是1394250507
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