mindspore/example/Bert_NEZHA_cnwiki/config.py

58 lines
1.8 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.
# ============================================================================
"""
network config setting, will be used in train.py
"""
from easydict import EasyDict as edict
import mindspore.common.dtype as mstype
from mindspore.model_zoo.Bert_NEZHA import BertConfig
bert_train_cfg = edict({
'epoch_size': 10,
'num_warmup_steps': 0,
'start_learning_rate': 1e-4,
'end_learning_rate': 0.0,
'decay_steps': 1000,
'power': 10.0,
'save_checkpoint_steps': 2000,
'keep_checkpoint_max': 10,
'checkpoint_prefix': "checkpoint_bert",
# please add your own dataset path
'DATA_DIR': "/your/path/examples.tfrecord",
# please add your own dataset schema path
'SCHEMA_DIR': "/your/path/datasetSchema.json"
})
bert_net_cfg = BertConfig(
batch_size=16,
seq_length=128,
vocab_size=21136,
hidden_size=1024,
num_hidden_layers=24,
num_attention_heads=16,
intermediate_size=4096,
hidden_act="gelu",
hidden_dropout_prob=0.0,
attention_probs_dropout_prob=0.0,
max_position_embeddings=512,
type_vocab_size=2,
initializer_range=0.02,
use_relative_positions=True,
input_mask_from_dataset=True,
token_type_ids_from_dataset=True,
dtype=mstype.float32,
compute_type=mstype.float16,
)