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Hello world, from verifai!
Browse files- .DS_Store +0 -0
- .gitattributes +34 -0
- README.md +41 -0
- config.json +36 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +0 -0
- tokenizer_config.json +16 -0
- vocab.json +0 -0
.DS_Store
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.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md
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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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# 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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config.json
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{
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"_name_or_path": "izhx/my-awesome-roberta",
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "Human",
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"1": "ChatGPT"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"ChatGPT": 1,
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"Human": 0
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.25.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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merges.txt
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:de2c7f8f590b0acd7866b18d5561b9d27e82d31a3dc24a8909658d2a8149ed94
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size 498657517
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special_tokens_map.json
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tokenizer.json
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tokenizer_config.json
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"tokenizer_class": "RobertaTokenizer",
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}
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vocab.json
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