wsqstar/bert-finetuned-weibo-luobokuaipao

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bert-finetuned-weibo-luobokuaipao

This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 1.1020
• —Accuracy: 0.5981

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 1e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.42.4
• —Pytorch 2.3.1+cu121
• —Datasets 2.20.0
• —Tokenizers 0.19.1

@misc{wang2024recentsurgepublictransportation,
      title={Recent Surge in Public Interest in Transportation: Sentiment Analysis of Baidu Apollo Go Using Weibo Data}, 
      author={Shiqi Wang and Zhouye Zhao and Yuhang Xie and Mingchuan Ma and Zirui Chen and Zeyu Wang and Bohao Su and Wenrui Xu and Tianyi Li},
      year={2024},
      eprint={2408.10088},
      archivePrefix={arXiv},
      primaryClass={cs.SI},
      url={https://arxiv.org/abs/2408.10088}, 
}