mindspore/example/bert_clue/evaluation_config.py

54 lines
1.6 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/evaluation.tfrecord',
'schema_file': '/your/path/schema.json',
'finetune_ckpt': '/your/path/your.ckpt',
'use_crf': False,
'clue_benchmark': False,
})
bert_net_cfg = BertConfig(
batch_size=16 if not cfg.clue_benchmark else 1,
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=0.0,
attention_probs_dropout_prob=0.0,
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,
)