mindspore/example/bert_clue/finetune_config.py

120 lines
3.0 KiB
Python

# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""
config settings, will be used in finetune.py
"""
from easydict import EasyDict as edict
import mindspore.common.dtype as mstype
from mindspore.model_zoo.Bert_NEZHA import BertConfig
cfg = edict({
'task': 'NER',
'num_labels': 41,
'data_file': '/your/path/train.tfrecord',
'schema_file': '/your/path/schema.json',
'epoch_num': 5,
'ckpt_prefix': 'bert',
'ckpt_dir': None,
'pre_training_ckpt': '/your/path/pre_training.ckpt',
'use_crf': False,
'optimizer': 'Lamb',
'AdamWeightDecayDynamicLR': edict({
'learning_rate': 2e-5,
'end_learning_rate': 1e-7,
'power': 1.0,
'weight_decay': 1e-5,
'eps': 1e-6,
}),
'Lamb': edict({
'start_learning_rate': 2e-5,
'end_learning_rate': 1e-7,
'power': 1.0,
'decay_filter': lambda x: False,
}),
'Momentum': edict({
'learning_rate': 2e-5,
'momentum': 0.9,
}),
})
bert_net_cfg = BertConfig(
batch_size=16,
seq_length=128,
vocab_size=21128,
hidden_size=768,
num_hidden_layers=12,
num_attention_heads=12,
intermediate_size=3072,
hidden_act="gelu",
hidden_dropout_prob=0.1,
attention_probs_dropout_prob=0.1,
max_position_embeddings=512,
type_vocab_size=2,
initializer_range=0.02,
use_relative_positions=False,
input_mask_from_dataset=True,
token_type_ids_from_dataset=True,
dtype=mstype.float32,
compute_type=mstype.float16,
)
tag_to_index = {
"O": 0,
"S_address": 1,
"B_address": 2,
"M_address": 3,
"E_address": 4,
"S_book": 5,
"B_book": 6,
"M_book": 7,
"E_book": 8,
"S_company": 9,
"B_company": 10,
"M_company": 11,
"E_company": 12,
"S_game": 13,
"B_game": 14,
"M_game": 15,
"E_game": 16,
"S_government": 17,
"B_government": 18,
"M_government": 19,
"E_government": 20,
"S_movie": 21,
"B_movie": 22,
"M_movie": 23,
"E_movie": 24,
"S_name": 25,
"B_name": 26,
"M_name": 27,
"E_name": 28,
"S_organization": 29,
"B_organization": 30,
"M_organization": 31,
"E_organization": 32,
"S_position": 33,
"B_position": 34,
"M_position": 35,
"E_position": 36,
"S_scene": 37,
"B_scene": 38,
"M_scene": 39,
"E_scene": 40,
"<START>": 41,
"<STOP>": 42
}