Awesome

GAU-α

基于Gated Attention Unit的Transformer模型（尝鲜版）

介绍

评测

CLUE榜单分类任务结果

	iflytek	tnews	afqmc	cmnli	ocnli	wsc	csl
BERT	60.06	56.80	72.41	79.56	73.93	78.62	83.93
RoBERTa	60.64	58.06	74.05	81.24	76.00	87.50	84.50
RoFormer	60.91	57.54	73.52	80.92	76.07	86.84	84.63
RoFormerV2<sup>*</sup>	60.87	56.54	72.75	80.34	75.36	80.92	84.67
GAU-α	61.41	57.76	74.17	81.82	75.86	79.93	85.67

CLUE榜单阅读理解和NER结果

	cmrc2018	c3	chid	cluener
BERT	56.17	60.54	85.69	79.45
RoBERTa	56.54	67.66	86.71	79.47
RoFormer	56.26	67.24	86.57	79.72
RoFormerV2<sup>*</sup>	57.91	64.62	85.09	81.08
GAU-α	58.09	68.24	87.91	80.01

使用

需要bert4keras>=0.11.3。参考代码：

from bert4keras.models import build_transformer_model
from models import GAU_alpha

gau_model = build_transformer_model(
    config_path=config_path,
    checkpoint_path=checkpoint_path,
    model=GAU_alpha,
)

下载

Base版：chinese_GAU-alpha-char_L-24_H-768.zip、百度云(提取码：0d4s)

引用

Bibtex：

@techreport{gau-alpha,
  title={GAU-α: GAU-based Transformers for NLP - ZhuiyiAI},
  author={Jianlin Su, Shengfeng Pan, Bo Wen, Yunfeng Liu},
  year={2022},
  url="https://github.com/ZhuiyiTechnology/GAU-alpha",
}

联系

邮箱：ai@wezhuiyi.com
追一科技：https://zhuiyi.ai