Edit model card

Erlangshen-Roberta-110M-Sentiment

简介 Brief Introduction

中文的RoBERTa-wwm-ext-base在数个情感分析任务微调后的版本

This is the fine-tuned version of the Chinese RoBERTa-wwm-ext-base model on several sentiment analysis datasets.

模型分类 Model Taxonomy

需求 Demand 任务 Task 系列 Series 模型 Model 参数 Parameter 额外 Extra
通用 General 自然语言理解 NLU 二郎神 Erlangshen Roberta 110M 情感分析 Sentiment

模型信息 Model Information

基于chinese-roberta-wwm-ext-base,我们在收集的8个中文领域的情感分析数据集,总计227347个样本上微调了一个Semtiment版本。

Based on chinese-roberta-wwm-ext-base, we fine-tuned a sentiment analysis version on 8 Chinese sentiment analysis datasets, with totaling 227,347 samples.

下游效果 Performance

模型 Model ASAP-SENT ASAP-ASPECT ChnSentiCorp
Erlangshen-Roberta-110M-Sentiment 97.77 97.31 96.61
Erlangshen-Roberta-330M-Sentiment 97.9 97.51 96.66
Erlangshen-MegatronBert-1.3B-Sentiment 98.1 97.8 97

使用 Usage

from transformers import BertForSequenceClassification
from transformers import BertTokenizer
import torch

tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-110M-Sentiment')
model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-110M-Sentiment')

text='今天心情不好'

output=model(torch.tensor([tokenizer.encode(text)]))
print(torch.nn.functional.softmax(output.logits,dim=-1))

引用 Citation

如果您在您的工作中使用了我们的模型,可以引用我们的论文

If you are using the resource for your work, please cite the our paper:

@article{fengshenbang,
  author    = {Junjie Wang and Yuxiang Zhang and Lin Zhang and Ping Yang and Xinyu Gao and Ziwei Wu and Xiaoqun Dong and Junqing He and Jianheng Zhuo and Qi Yang and Yongfeng Huang and Xiayu Li and Yanghan Wu and Junyu Lu and Xinyu Zhu and Weifeng Chen and Ting Han and Kunhao Pan and Rui Wang and Hao Wang and Xiaojun Wu and Zhongshen Zeng and Chongpei Chen and Ruyi Gan and Jiaxing Zhang},
  title     = {Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence},
  journal   = {CoRR},
  volume    = {abs/2209.02970},
  year      = {2022}
}

也可以引用我们的网站:

You can also cite our website:

@misc{Fengshenbang-LM,
  title={Fengshenbang-LM},
  author={IDEA-CCNL},
  year={2021},
  howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
}
Downloads last month
3,115
Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.