-
Notifications
You must be signed in to change notification settings - Fork 3k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
* add llama&qwen dpo * add * add dpo * fix bug * add
- Loading branch information
Showing
19 changed files
with
1,513 additions
and
80 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,100 @@ | ||
| # Copyright (c) 2024 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. | ||
|
|
||
|
|
||
| from dataclasses import dataclass, field | ||
| from typing import Optional | ||
|
|
||
| from paddlenlp.trainer import TrainingArguments | ||
|
|
||
|
|
||
| def add_start_docstrings(*docstr): | ||
| """Adds docstrings for a function.""" | ||
|
|
||
| def docstring_decorator(fn): | ||
| fn.__doc__ = "".join(docstr) + (fn.__doc__ if fn.__doc__ is not None else "") | ||
| return fn | ||
|
|
||
| return docstring_decorator | ||
|
|
||
|
|
||
| @dataclass | ||
| @add_start_docstrings(TrainingArguments.__doc__) | ||
| class DPOTrainingArguments(TrainingArguments): | ||
| """DPOTrainingArguments""" | ||
|
|
||
| unified_checkpoint: bool = field( | ||
| default=True, | ||
| metadata={"help": "Enable fused linear grad add strategy."}, | ||
| ) | ||
| unified_checkpoint_config: Optional[str] = field( | ||
| default="", | ||
| metadata={"help": "Configs to unify hybrid parallel checkpoint.\n"}, | ||
| ) | ||
| dpo_beta: float = field(default=0.1, metadata={"help": "the beta parameter for DPO loss"}) | ||
| dpo_label_smoothing: float = field(default=0.0, metadata={"help": "label_smoothing ratio"}) | ||
| dpo_loss_type: str = field(default="sigmoid", metadata={"help": "DPO loss type"}) | ||
|
|
||
|
|
||
| @dataclass | ||
| class DPODataArgument: | ||
| """DataArgument""" | ||
|
|
||
| train_dataset_path: str = field(default="./data/train.jsonl", metadata={"help": "Path to the train dataset dir."}) | ||
| dev_dataset_path: str = field(default="./data/dev.jsonl", metadata={"help": "Path to the dev dataset dir."}) | ||
| max_seq_len: int = field(default=4096, metadata={"help": "Maximum sequence length."}) | ||
| max_prompt_len: int = field(default=2048, metadata={"help": "Maximum prompt length."}) | ||
| autotuner_benchmark: bool = field( | ||
| default=False, | ||
| metadata={"help": "Whether to run benchmark by autotuner. True for from_scratch."}, | ||
| ) | ||
| benchmark: bool = field( | ||
| default=False, | ||
| metadata={"help": "Whether to run benchmark by autotuner. True for from_scratch."}, | ||
| ) | ||
| greedy_intokens: bool = field( | ||
| default=True, | ||
| metadata={"help": "Whether apply greedy intokens."}, | ||
| ) | ||
| buffer_size: int = field(default=500, metadata={"help": "Buffer size for greedy_intokens strategy."}) | ||
|
|
||
|
|
||
| @dataclass | ||
| class DPOModelArgument: | ||
| """ModelArgument""" | ||
|
|
||
| model_name_or_path: str = field( | ||
| default=None, metadata={"help": "Pretrained model name or path to local directory."} | ||
| ) | ||
| tokenizer_name_or_path: Optional[str] = field( | ||
| default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"} | ||
| ) | ||
| use_flash_attention: bool = field(default=False, metadata={"help": "Whether to use flash attention"}) | ||
| recompute_granularity: str = field( | ||
| default="full", | ||
| metadata={ | ||
| "help": "The granularity of recompute training can be selected as `full` or `full_attn` or `core_attn`." | ||
| }, | ||
| ) | ||
| use_attn_mask_start_row_indices: bool = field( | ||
| default=False, metadata={"help": "Whether to use attn_mask_start_row_indices in flash attention."} | ||
| ) | ||
| virtual_pp_degree: int = field( | ||
| default=1, | ||
| metadata={"help": "virtual_pp_degree"}, | ||
| ) | ||
| sequence_parallel: bool = field( | ||
| default=False, | ||
| metadata={"help": "whether to use sequence parallel"}, | ||
| ) |
Oops, something went wrong.