Erlangshen Roberta 330M Sentiment

🚀 Erlangshen-Roberta-330M-Sentiment

This is a fine-tuned version of the Chinese RoBERTa-wwm-ext-large model on several sentiment analysis datasets, aiming to provide high - performance sentiment analysis capabilities for Chinese text.

🚀 Quick Start

• Main Page: Fengshenbang
• Github: Fengshenbang-LM

✨ Features

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

📚 Documentation

Model Taxonomy

Model Information

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

Performance

💻 Usage Examples

Basic Usage

from transformers import BertForSequenceClassification
from transformers import BertTokenizer
import torch

tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')
model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')

text='今天心情不好'

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

📄 License

This project is licensed under the Apache - 2.0 license.

📚 Citation

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

@article{fengshenbang,
  author    = {Jiaxing Zhang and Ruyi Gan and 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},
  title     = {Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence},
  journal   = {CoRR},
  volume    = {abs/2209.02970},
  year      = {2022}
}

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}},
}