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Description

Add decay_steps option to finetuning for more precise adjustment on learning rate.

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paddle-bot bot commented Apr 10, 2024

Thanks for your contribution!

@wawltor wawltor merged commit bd25e0c into PaddlePaddle:develop Apr 10, 2024
wawltor pushed a commit that referenced this pull request May 24, 2024
* [XPU] llama add xpu support (#8282)

* [XPU] llama add xpu support

* fix

* use try import

* fix

* refine

* refine

* refine

* refine

* update (#8399)

* [LLM] Support fuse attention q, k, v weights  (#8202)

1. add use-interface & fuse action

1.1. modify 1., code order

2. switch to name_mapping

3. solve tp branch

3.2 follow hui, handel qkv separately

3.3 handle pdparams

3.4 from torch

3.5 abandon low_cpu_mem_usage

3.6 solve shard branch

* 3.6.1 solve shard branch after rebase develop

* code clean

* remove debug comment

* Redefine fuse and split functions

* Redefine fuse and split functions

* comment and fix

* update method

* update QKV fuse and split

* support fuse weights in multi-files

* add precision compare

* simplify function call

* support use_fast_ffn

* clean modeling and configuration

* add test for gpt and opt

* fix tp_actions get

* add fast_ffn test

* add Qwen2Moe

* Revert "add Qwen2Moe"

This reverts commit 113b883.

* add test for split

* update doc

* update filter_dict_keys

---------

Co-authored-by: Zii <[email protected]>

* [LLM] Fix fuse or split with same key (#8378)

* fix fuse or split with same key

* fix

* fix eps

* update format

* [LLM] add decay steps option for finetuning (#8251)

* [LLM] add memory stats to logger of trainer (#8269)

* [Distributed] fix lora (#8325)

* [LLM] fix lora target modules on llama (#8372)

* [Distributed] metric calculation supports tp logits (#8370)

* Update model_utils.py

* Update model_utils.py

* Update model_utils.py

---------

Co-authored-by: Jianbang Yang <[email protected]>
Co-authored-by: DrownFish19 <[email protected]>
Co-authored-by: Zii <[email protected]>
Co-authored-by: Tian <[email protected]>
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3 participants