wehub-resource-sync
93 lines
4.0 KiB
Python
93 lines
4.0 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# 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.
|
|
|
|
import argparse
|
|
|
|
|
|
def parse_args():
|
|
parser = argparse.ArgumentParser(description=__doc__)
|
|
parser.add_argument("--model_type", default=None, type=str, required=True, help="Type of pre-trained model.")
|
|
parser.add_argument(
|
|
"--model_name_or_path",
|
|
default=None,
|
|
type=str,
|
|
required=True,
|
|
help="Path to pre-trained model or shortcut name of model.",
|
|
)
|
|
parser.add_argument(
|
|
"--output_dir",
|
|
default=None,
|
|
type=str,
|
|
required=True,
|
|
help="The output directory where the model predictions and checkpoints will be written.",
|
|
)
|
|
parser.add_argument(
|
|
"--max_seq_length",
|
|
default=128,
|
|
type=int,
|
|
help="The maximum total input sequence length after tokenization. Sequences longer "
|
|
"than this will be truncated, sequences shorter will be padded.",
|
|
)
|
|
parser.add_argument("--batch_size", default=8, type=int, help="Batch size per GPU/CPU for training.")
|
|
parser.add_argument("--learning_rate", default=5e-5, type=float, help="The initial learning rate for Adam.")
|
|
parser.add_argument("--weight_decay", default=0.0, type=float, help="Weight decay if we apply some.")
|
|
parser.add_argument("--adam_epsilon", default=1e-8, type=float, help="Epsilon for Adam optimizer.")
|
|
parser.add_argument("--max_grad_norm", default=1.0, type=float, help="Max gradient norm.")
|
|
parser.add_argument("--num_train_epochs", default=3, type=int, help="Total number of training epochs to perform.")
|
|
parser.add_argument(
|
|
"--max_steps",
|
|
default=-1,
|
|
type=int,
|
|
help="If > 0: set total number of training steps to perform. Override num_train_epochs.",
|
|
)
|
|
parser.add_argument(
|
|
"--warmup_proportion",
|
|
default=0.0,
|
|
type=float,
|
|
help="Proportion of training steps to perform linear learning rate warmup for.",
|
|
)
|
|
parser.add_argument("--logging_steps", type=int, default=500, help="Log every X updates steps.")
|
|
parser.add_argument("--save_steps", type=int, default=500, help="Save checkpoint every X updates steps.")
|
|
parser.add_argument("--seed", type=int, default=42, help="random seed for initialization")
|
|
parser.add_argument(
|
|
"--device",
|
|
choices=["cpu", "gpu", "npu"],
|
|
default="gpu",
|
|
help="Select which device to train model, defaults to gpu.",
|
|
)
|
|
parser.add_argument(
|
|
"--doc_stride",
|
|
type=int,
|
|
default=128,
|
|
help="When splitting up a long document into chunks, how much stride to take between chunks.",
|
|
)
|
|
parser.add_argument(
|
|
"--n_best_size",
|
|
type=int,
|
|
default=20,
|
|
help="The total number of n-best predictions to generate in the nbest_predictions.json output file.",
|
|
)
|
|
parser.add_argument("--max_query_length", type=int, default=64, help="Max query length.")
|
|
parser.add_argument("--max_answer_length", type=int, default=30, help="Max answer length.")
|
|
parser.add_argument(
|
|
"--do_lower_case",
|
|
action="store_false",
|
|
help="Whether to lower case the input text. Should be True for uncased models and False for cased models.",
|
|
)
|
|
parser.add_argument("--verbose", action="store_true", help="Whether to output verbose log.")
|
|
parser.add_argument("--do_train", action="store_true", help="Whether to train the model.")
|
|
parser.add_argument("--do_predict", action="store_true", help="Whether to predict.")
|
|
args = parser.parse_args()
|
|
return args
|