forked from mindspore-Ecosystem/mindspore
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""
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network config setting, will be used in train.py
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"""
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from easydict import EasyDict as edict
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import mindspore.common.dtype as mstype
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from mindspore.model_zoo.Bert_NEZHA import BertConfig
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bert_train_cfg = edict({
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'epoch_size': 10,
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'num_warmup_steps': 0,
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'start_learning_rate': 1e-4,
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'end_learning_rate': 0.0,
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'decay_steps': 1000,
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'power': 10.0,
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'save_checkpoint_steps': 2000,
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'keep_checkpoint_max': 10,
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'checkpoint_prefix': "checkpoint_bert",
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# please add your own dataset path
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'DATA_DIR': "/your/path/examples.tfrecord",
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# please add your own dataset schema path
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'SCHEMA_DIR': "/your/path/datasetSchema.json"
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})
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bert_net_cfg = BertConfig(
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batch_size=16,
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seq_length=128,
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vocab_size=21136,
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hidden_size=1024,
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num_hidden_layers=24,
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num_attention_heads=16,
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intermediate_size=4096,
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hidden_act="gelu",
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hidden_dropout_prob=0.0,
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attention_probs_dropout_prob=0.0,
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max_position_embeddings=512,
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type_vocab_size=2,
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initializer_range=0.02,
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use_relative_positions=True,
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input_mask_from_dataset=True,
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token_type_ids_from_dataset=True,
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dtype=mstype.float32,
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compute_type=mstype.float16,
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)
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