clovexcwz / ner_demo Goto Github PK

I am so sorry to found that your f1score and recall are wrong.
yours:
f1score = f1_score(pre, test_label, average='macro')
recall = recall_score(pre, test_label, average='macro')

but:
def f1_score(y_true, y_pred, *, labels=None, pos_label=1, average='binary',
sample_weight=None, zero_division="warn")
def recall_score(y_true, y_pred, *, labels=None, pos_label=1, average='binary',
sample_weight=None, zero_division="warn")

the position of y_true and y_pred is reversed.
it is cost a long time for finding this difference when i use my DIY metricts.

为什么不对比BERT-IDCNN-CRF模型呢

遇到了这个问题，折腾了好久。
这是keras-transformer版本问题，换成0.31.0就ok了。
给后来者留个提醒。

想问一下keras-contrib怎么下载0.0.2版本 github上只有最新的版本

你好，这是什么原因造成的呢？
Traceback (most recent call last):
File "D:/研究生/NER_DEMO-master/NER_DEMO-master/train.py", line 108, in
info_list = train_sample(train_model='BERTBILSTMCRF', epochs=15, log=log)
File "D:/研究生/NER_DEMO-master/NER_DEMO-master/train.py", line 52, in train_sample
model = model_class.creat_model()
File "D:\研究生\NER_DEMO-master\NER_DEMO-master\Model\BERT_BILSTM_CRF.py", line 51, in creat_model
x = self.crf(x)
File "D:\Application\python3.6\lib\site-packages\keras\engine\base_layer.py", line 443, in call
previous_mask = _collect_previous_mask(inputs)
File "D:\Application\python3.6\lib\site-packages\keras\engine\base_layer.py", line 1311, in _collect_previous_mask
mask = node.output_masks[tensor_index]
AttributeError: 'Node' object has no attribute 'output_masks'

while training, BERTBILSTMCRF,when create model, it raise:
TypeError: get_encoders() got an unexpected keyword argument 'use_adapter'

Traceback (most recent call last):
File "train.py", line 101, in
info_list = train_sample(train_model=model, epochs=10, log=log)
File "train.py", line 51, in train_sample
model = model_class.creat_model()
File "/root/NER_DEMO-master/Model/BERT_BILSTM_CRF.py", line 39, in creat_model
trainable=True)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/keras_bert/loader.py", line 169, in load_trained_model_from_checkpoint
**kwargs)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/keras_bert/loader.py", line 58, in build_model_from_config
**kwargs)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/keras_bert/bert.py", line 91, in get_model
dropout_rate=dropout_rate,
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/keras_bert/layers/embedding.py", line 56, in get_embedding
)(embed_layer)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 663, in call
inputs, outputs, args, kwargs)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1708, in set_connectivity_metadata
input_tensors=inputs, output_tensors=outputs, arguments=kwargs)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1796, in _add_inbound_node
input_tensors)
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/util/nest.py", line 515, in map_structure
structure[0], [func(*x) for x in entries],
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/util/nest.py", line 515, in
structure[0], [func(*x) for x in entries],
File "/root/miniconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1795, in
inbound_layers = nest.map_structure(lambda t: t._keras_history.layer,
AttributeError: 'tuple' object has no attribute 'layer'

执行这句话
model = keras_bert.load_trained_model_from_checkpoint(config_file=config_path,
checkpoint_file=checkpoint_path,
)
报如下错误：
AttributeError: 'tuple' object has no attribute 'layer'

我训练了5Epochs，F1-score达到0.96，但是我写了代码预测测试集中的几句话，结果全是0

跑bert时 报错了 本人小白 求大佬帮忙 球球了

我按照data2的格式修改了我的数据集 并且在vocab.py里修改了实体类别 但我试验抛出的结果显示正确率没问题 但召回率和F值只有0.0几 请问下问题出在那里 歇息大佬