metadata
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- NLI
inference: false
Erlangshen-Roberta-110M-Semtiment, model (Chinese),one model of Fengshenbang-LM.
We collect 8 paraphrace datasets in the Chinese domain for finetune, with a total of 227347 samples. Our model is mainly based on roberta
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))
Scores on downstream chinese tasks
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 |
Citation
If you find the resource is useful, please cite the following website in your paper.
@misc{Fengshenbang-LM,
title={Fengshenbang-LM},
author={IDEA-CCNL},
year={2021},
howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
}