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license: mit
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# Model Card for `Hello-SimpleAI/chatgpt-detector-roberta`
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This model is trained on **the mix of full-text and splitted sentences** of `answer`s from [Hello-SimpleAI/HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3).
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More details refer to [arxiv: 2301.07597](https://arxiv.org/abs/2301.07597) and Gtihub project [Hello-SimpleAI/chatgpt-comparison-detection](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection).
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The base checkpoint is [roberta-base](https://huggingface.co/roberta-base).
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We train it with all [Hello-SimpleAI/HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3) data (without held-out) for 1 epoch.
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(1-epoch is consistent with the experiments in [our paper](https://arxiv.org/abs/2301.07597).)
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## Citation
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Checkout this papaer [arxiv: 2301.07597](https://arxiv.org/abs/2301.07597)
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```
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@article{guo-etal-2023-hc3,
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title = "How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection",
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author = "Guo, Biyang and
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Zhang, Xin and
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Wang, Ziyuan and
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Jiang, Minqi and
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Nie, Jinran and
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Ding, Yuxuan and
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Yue, Jianwei and
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Wu, Yupeng",
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journal={arXiv preprint arxiv:2301.07597}
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year = "2023",
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}
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```
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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license: mit
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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