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数据中###位置超过实体数目的问题

percent4,您好,看了您的仓库,收获非常大,在使用过程中发现了一个问题:

image

数据集中### 表示实体,但是句子中出现了多次实体,导致无法确定实体在句子中的具体位置,请问可以提供原始的文本数据,进行一下筛选么?筛选成每个句子只挖空两个位置,将大于两个位置的句子进行舍弃。

谢谢!

博主您好

我已经看了您的几片关于NLP的文章。但是作为一个初学者,实践起来面对您的项目有点不知从何下手。比如训练模型怎么跑通,您有什么建议吗?

KeyError: 'val_accuracy'

RuntimeWarning: Early stopping conditioned on metric val_accuracy which is not available. Available metrics are: val_loss,val_acc,loss,acc
(self.monitor, ','.join(list(logs.keys()))), RuntimeWarning

请教bert的特征提取用法

看文章,知道是用bert来提取特征,但是如何做的呢,我想学习,

还有fine tuning的方法又是如何做的呢,多谢多谢!

请教下源文件中使用的tensorflow版本号

运行model_train.py时,会报错:module 'tensorflow' has no attribute 'logging',原因是我使用的tensorflow2.0+中没有logging,所以想请问下源文件中的tensorflow版本号

人物实体的位置

使用bert进行特征提取时,需要考虑每个词距离人物实体的相对位置吗。

bert文件缺失

您好,跑您的代码发现
model_dir = os.path.join(file_path, 'chinese_L-12_H-768_A-12')
config_name = os.path.join(model_dir, 'bert_config.json')
ckpt_name = os.path.join(model_dir, 'bert_model.ckpt')
vocab_file = os.path.join(model_dir, 'vocab.txt')
这些文件代码里面没有

model_predict.py input_1 shape error

I:BERT_VEC:[graph:opt:144]:write graph to a tmp file: ./tmp_graph11
Traceback (most recent call last):
File "model_predict.py", line 48, in
predicted = model.predict(x_train)

ValueError: Error when checking input: expected input_1 to have shape (128, 768) but got array with shape (80, 768)

pip install h5py==2.10

          pip install h5py==2.10

Hello,when I run you code,I meet the problem as follow,can you give me some help?Thank you very much!
line 72, in as_bytes(bytes_or_text,))
TypeError: Expected binary or unicode string, got None

Originally posted by @longkeyy in #9 (comment)

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