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--- |
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base_model: bert-base-chinese |
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metrics: |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-finetuned-weibo-luobokuaipao |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-finetuned-weibo-luobokuaipao |
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1020 |
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- Accuracy: 0.5981 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 243 | 1.0453 | 0.5519 | |
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| No log | 2.0 | 486 | 0.9954 | 0.5796 | |
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| 0.9964 | 3.0 | 729 | 1.0374 | 0.6074 | |
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| 0.9964 | 4.0 | 972 | 1.0489 | 0.6019 | |
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| 0.6111 | 5.0 | 1215 | 1.1020 | 0.5981 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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``` |
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@misc{wang2024recentsurgepublictransportation, |
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title={Recent Surge in Public Interest in Transportation: Sentiment Analysis of Baidu Apollo Go Using Weibo Data}, |
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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}, |
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year={2024}, |
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eprint={2408.10088}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.SI}, |
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url={https://arxiv.org/abs/2408.10088}, |
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} |
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``` |