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Merged
merged 1 commit into from
Nov 29, 2017
Merged

Refine NER #504

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23 changes: 13 additions & 10 deletions sequence_tagging_for_ner/network_conf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ def ner_net(word_dict_len, label_dict_len, stack_num=2, is_train=True):
mark_dict_len = 2
word_dim = 50
mark_dim = 5
hidden_dim = 128
hidden_dim = 300

word = paddle.layer.data(
name="word",
Expand All @@ -23,27 +23,26 @@ def ner_net(word_dict_len, label_dict_len, stack_num=2, is_train=True):
name="mark",
type=paddle.data_type.integer_value_sequence(mark_dict_len))
mark_embedding = paddle.layer.embedding(
input=mark,
size=mark_dim,
param_attr=paddle.attr.Param(initial_std=math.sqrt(1. / word_dim)))
input=mark, size=mark_dim, param_attr=paddle.attr.Param(initial_std=0.))

word_caps_vector = paddle.layer.concat(
input=[word_embedding, mark_embedding])

mix_hidden_lr = 1e-3
rnn_para_attr = paddle.attr.Param(initial_std=0.0, learning_rate=0.1)
hidden_para_attr = paddle.attr.Param(
initial_std=1 / math.sqrt(hidden_dim), learning_rate=mix_hidden_lr)
initial_std=1. / math.sqrt(hidden_dim) / 3, learning_rate=mix_hidden_lr)

# the first forward and backward rnn layer share the
# input-to-hidden mappings.
hidden = paddle.layer.fc(
name="__hidden00__",
size=hidden_dim,
act=paddle.activation.Tanh(),
bias_attr=paddle.attr.Param(initial_std=1.),
bias_attr=paddle.attr.Param(initial_std=1. / math.sqrt(hidden_dim) / 3),
input=word_caps_vector,
param_attr=hidden_para_attr)
param_attr=paddle.attr.Param(initial_std=1. / math.sqrt(hidden_dim) /
3))

fea = []
for direction in ["fwd", "bwd"]:
Expand All @@ -68,7 +67,7 @@ def ner_net(word_dict_len, label_dict_len, stack_num=2, is_train=True):

rnn_fea = paddle.layer.fc(
size=hidden_dim,
bias_attr=paddle.attr.Param(initial_std=1.),
bias_attr=paddle.attr.Param(initial_std=1. / math.sqrt(hidden_dim) / 3),
act=paddle.activation.STanh(),
input=fea,
param_attr=[hidden_para_attr, rnn_para_attr] * 2)
Expand All @@ -85,7 +84,8 @@ def ner_net(word_dict_len, label_dict_len, stack_num=2, is_train=True):
bias_attr=False,
input=rnn_fea,
act=paddle.activation.Linear(),
param_attr=rnn_para_attr)
param_attr=paddle.attr.Param(initial_std=1. / math.sqrt(hidden_dim) /
3))

if is_train:
target = paddle.layer.data(
Expand All @@ -96,7 +96,10 @@ def ner_net(word_dict_len, label_dict_len, stack_num=2, is_train=True):
size=label_dict_len,
input=emission,
label=target,
param_attr=paddle.attr.Param(name="crfw", initial_std=1e-3))
param_attr=paddle.attr.Param(
name="crfw",
initial_std=1. / math.sqrt(hidden_dim) / 3,
learning_rate=mix_hidden_lr))

crf_dec = paddle.layer.crf_decoding(
size=label_dict_len,
Expand Down
8 changes: 4 additions & 4 deletions sequence_tagging_for_ner/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,8 +16,8 @@ def main(train_data_file,
target_file,
emb_file,
model_save_dir,
num_passes=10,
batch_size=32):
num_passes=100,
batch_size=64):
if not os.path.exists(model_save_dir):
os.mkdir(model_save_dir)

Expand Down Expand Up @@ -75,10 +75,10 @@ def main(train_data_file,

def event_handler(event):
if isinstance(event, paddle.event.EndIteration):
if event.batch_id % 1 == 0:
if event.batch_id % 5 == 0:
logger.info("Pass %d, Batch %d, Cost %f, %s" % (
event.pass_id, event.batch_id, event.cost, event.metrics))
if event.batch_id % 1 == 0:
if event.batch_id % 50 == 0:
result = trainer.test(reader=test_reader, feeding=feeding)
logger.info("\nTest with Pass %d, Batch %d, %s" %
(event.pass_id, event.batch_id, result.metrics))
Expand Down