Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly
Appearance settings

Commit 27bef16

Browse filesBrowse files
bojonebojone
authored
Add files via upload
1 parent 306c867 commit 27bef16
Copy full SHA for 27bef16

File tree

Expand file treeCollapse file tree

6 files changed

+25
-25
lines changed
Open diff view settings
Filter options
Expand file treeCollapse file tree

6 files changed

+25
-25
lines changed
Open diff view settings
Collapse file

‎CLUENER_CRF.py‎

Copy file name to clipboardExpand all lines: CLUENER_CRF.py
+4-4Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -17,8 +17,8 @@
1717

1818
maxlen = 256
1919
epochs = 10
20-
batch_size = 32
21-
learning_rate = 2e-5 # bert_layers越小，学习率应该要越大
20+
batch_size = 16
21+
learning_rate = 2e-5
2222
crf_lr_multiplier = 1000 # 必要时扩大CRF层的学习率
2323
categories = set()
2424

@@ -158,7 +158,7 @@ def on_epoch_end(self, epoch, logs=None):
158158
# 保存最优
159159
if f1 >= self.best_val_f1:
160160
self.best_val_f1 = f1
161-
model.save_weights('./best_model.weights')
161+
model.save_weights('./best_model_cluener_crf.weights')
162162
print(
163163
'valid: f1: %.5f, precision: %.5f, recall: %.5f, best f1: %.5f\n' %
164164
(f1, precision, recall, self.best_val_f1)
@@ -200,6 +200,6 @@ def predict_to_file(in_file, out_file):
200200

201201
else:
202202

203-
model.load_weights('./best_model.weights')
203+
model.load_weights('./best_model_cluener_crf.weights')
204204
NER.trans = K.eval(CRF.trans)
205205
# predict_to_file('/root/ner/cluener/test.json', 'cluener_test.json')
Collapse file

‎CLUENER_GlobalPointer.py‎

Copy file name to clipboardExpand all lines: CLUENER_GlobalPointer.py
+4-4Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
#! -*- coding: utf-8 -*-
2-
# 用全局归一化指针做中文命名实体识别
2+
# 用GlobalPointer做中文命名实体识别
33
# 数据集 https://github.com/CLUEbenchmark/CLUENER2020
44

55
import json
@@ -162,7 +162,7 @@ def on_epoch_end(self, epoch, logs=None):
162162
# 保存最优
163163
if f1 >= self.best_val_f1:
164164
self.best_val_f1 = f1
165-
model.save_weights('./best_model.weights')
165+
model.save_weights('./best_model_cluener_globalpointer.weights')
166166
print(
167167
'valid: f1: %.5f, precision: %.5f, recall: %.5f, best f1: %.5f\n' %
168168
(f1, precision, recall, self.best_val_f1)
@@ -199,10 +199,10 @@ def predict_to_file(in_file, out_file):
199199
train_generator.forfit(),
200200
steps_per_epoch=len(train_generator),
201201
epochs=epochs,
202-
callbacks=[evaluator],
202+
callbacks=[evaluator]
203203
)
204204

205205
else:
206206

207-
model.load_weights('./best_model.weights')
207+
model.load_weights('./best_model_cluener_globalpointer.weights')
208208
# predict_to_file('/root/ner/cluener/test.json', 'cluener_test.json')
Collapse file

‎CMeEE_CRF.py‎

Copy file name to clipboardExpand all lines: CMeEE_CRF.py
+5-5Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -17,8 +17,8 @@
1717

1818
maxlen = 256
1919
epochs = 10
20-
batch_size = 32
21-
learning_rate = 2e-5 # bert_layers越小，学习率应该要越大
20+
batch_size = 16
21+
learning_rate = 2e-5
2222
crf_lr_multiplier = 1000 # 必要时扩大CRF层的学习率
2323
categories = set()
2424

@@ -155,7 +155,7 @@ def on_epoch_end(self, epoch, logs=None):
155155
# 保存最优
156156
if f1 >= self.best_val_f1:
157157
self.best_val_f1 = f1
158-
model.save_weights('./best_model.weights')
158+
model.save_weights('./best_model_cmeee_crf.weights')
159159
print(
160160
'valid: f1: %.5f, precision: %.5f, recall: %.5f, best f1: %.5f\n' %
161161
(f1, precision, recall, self.best_val_f1)
@@ -193,11 +193,11 @@ def predict_to_file(in_file, out_file):
193193
train_generator.forfit(),
194194
steps_per_epoch=len(train_generator),
195195
epochs=epochs,
196-
callbacks=[evaluator],
196+
callbacks=[evaluator]
197197
)
198198

199199
else:
200200

201-
model.load_weights('./best_model.weights')
201+
model.load_weights('./best_model_cmeee_crf.weights')
202202
NER.trans = K.eval(CRF.trans)
203203
# predict_to_file('/root/ner/CMeEE/CMeEE_test.json', 'CMeEE_test.json')
Collapse file

‎CMeEE_GlobalPointer.py‎

Copy file name to clipboardExpand all lines: CMeEE_GlobalPointer.py
+4-4Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
#! -*- coding: utf-8 -*-
2-
# 用全局归一化指针做中文命名实体识别
2+
# 用GlobalPointer做中文命名实体识别
33
# 数据集 https://tianchi.aliyun.com/dataset/dataDetail?dataId=95414
44

55
import json
@@ -159,7 +159,7 @@ def on_epoch_end(self, epoch, logs=None):
159159
# 保存最优
160160
if f1 >= self.best_val_f1:
161161
self.best_val_f1 = f1
162-
model.save_weights('./best_model.weights')
162+
model.save_weights('./best_model_cmeee_globalpointer.weights')
163163
print(
164164
'valid: f1: %.5f, precision: %.5f, recall: %.5f, best f1: %.5f\n' %
165165
(f1, precision, recall, self.best_val_f1)
@@ -197,10 +197,10 @@ def predict_to_file(in_file, out_file):
197197
train_generator.forfit(),
198198
steps_per_epoch=len(train_generator),
199199
epochs=epochs,
200-
callbacks=[evaluator],
200+
callbacks=[evaluator]
201201
)
202202

203203
else:
204204

205-
model.load_weights('./best_model.weights')
205+
model.load_weights('./best_model_cmeee_globalpointer.weights')
206206
# predict_to_file('/root/ner/CMeEE/CMeEE_test.json', 'CMeEE_test.json')
Collapse file

‎PeopleDaily_CRF.py‎

Copy file name to clipboardExpand all lines: PeopleDaily_CRF.py
+4-4Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -16,8 +16,8 @@
1616

1717
maxlen = 256
1818
epochs = 10
19-
batch_size = 32
20-
learning_rate = 2e-5 # bert_layers越小，学习率应该要越大
19+
batch_size = 16
20+
learning_rate = 2e-5
2121
crf_lr_multiplier = 1000 # 必要时扩大CRF层的学习率
2222
categories = set()
2323

@@ -163,7 +163,7 @@ def on_epoch_end(self, epoch, logs=None):
163163
# 保存最优
164164
if f1 >= self.best_val_f1:
165165
self.best_val_f1 = f1
166-
model.save_weights('./best_model.weights')
166+
model.save_weights('./best_model_peopledaily_crf.weights')
167167
print(
168168
'valid: f1: %.5f, precision: %.5f, recall: %.5f, best f1: %.5f\n' %
169169
(f1, precision, recall, self.best_val_f1)
@@ -189,5 +189,5 @@ def on_epoch_end(self, epoch, logs=None):
189189

190190
else:
191191

192-
model.load_weights('./best_model.weights')
192+
model.load_weights('./best_model_peopledaily_crf.weights')
193193
NER.trans = K.eval(CRF.trans)
Collapse file

‎PeopleDaily_GlobalPointer.py‎

Copy file name to clipboardExpand all lines: PeopleDaily_GlobalPointer.py
+4-4Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
#! -*- coding: utf-8 -*-
2-
# 用全局归一化指针做中文命名实体识别
2+
# 用GlobalPointer做中文命名实体识别
33
# 数据集 http://s3.bmio.net/kashgari/china-people-daily-ner-corpus.tar.gz
44

55
import numpy as np
@@ -167,7 +167,7 @@ def on_epoch_end(self, epoch, logs=None):
167167
# 保存最优
168168
if f1 >= self.best_val_f1:
169169
self.best_val_f1 = f1
170-
model.save_weights('./best_model.weights')
170+
model.save_weights('./best_model_peopledaily_globalpointer.weights')
171171
print(
172172
'valid: f1: %.5f, precision: %.5f, recall: %.5f, best f1: %.5f\n' %
173173
(f1, precision, recall, self.best_val_f1)
@@ -188,9 +188,9 @@ def on_epoch_end(self, epoch, logs=None):
188188
train_generator.forfit(),
189189
steps_per_epoch=len(train_generator),
190190
epochs=epochs,
191-
callbacks=[evaluator],
191+
callbacks=[evaluator]
192192
)
193193

194194
else:
195195

196-
model.load_weights('./best_model.weights')
196+
model.load_weights('./best_model_peopledaily_globalpointer.weights')

0 commit comments

Comments
0 (0)
Morty Proxy This is a proxified and sanitized view of the page, visit original site.