---
base_model: bert-base-chinese
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-finetuned-weibo-luobokuaipao
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-finetuned-weibo-luobokuaipao

This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/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
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 243  | 1.0453          | 0.5519   |
| No log        | 2.0   | 486  | 0.9954          | 0.5796   |
| 0.9964        | 3.0   | 729  | 1.0374          | 0.6074   |
| 0.9964        | 4.0   | 972  | 1.0489          | 0.6019   |
| 0.6111        | 5.0   | 1215 | 1.1020          | 0.5981   |


### 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}, 
}
```