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  ---
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  datasets:
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  - Hello-SimpleAI/HC3
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- metrics:
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- - accuracy
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  datasets:
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  - Hello-SimpleAI/HC3
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+ language:
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+ - en
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+ pipeline_tag: text-classification
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+ tags:
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+ - chatgpt
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+ ---
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+
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+ # Model Card for `devloverumar/chatgpt-content-detector`
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+
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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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+
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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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+
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+
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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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+
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+ (1-epoch is consistent with the experiments in [our paper](https://arxiv.org/abs/2301.07597).)
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+
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+ ## Citation
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+
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+ Checkout this papaer [arxiv: 2301.07597](https://arxiv.org/abs/2301.07597)
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+
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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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+ ```