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--- |
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language: "c++" |
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tags: |
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- exbert |
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- authorship-identification |
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- fire2020 |
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- pan2020 |
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- ai-soco |
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- classification |
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license: "mit" |
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datasets: |
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- ai-soco |
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metrics: |
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- accuracy |
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--- |
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# ai-soco-c++-roberta-tiny-clas |
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## Model description |
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`ai-soco-c++-roberta-tiny` model fine-tuned on [AI-SOCO](https://sites.google.com/view/ai-soco-2020) task. |
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#### How to use |
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You can use the model directly after tokenizing the text using the provided tokenizer with the model files. |
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#### Limitations and bias |
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The model is limited to C++ programming language only. |
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## Training data |
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The model initialized from [`ai-soco-c++-roberta-tiny`](https://github.com/huggingface/transformers/blob/master/model_cards/aliosm/ai-soco-c++-roberta-tiny) model and trained using [AI-SOCO](https://sites.google.com/view/ai-soco-2020) dataset to do text classification. |
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## Training procedure |
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The model trained on Google Colab platform using V100 GPU for 10 epochs, 32 batch size, 512 max sequence length (sequences larger than 512 were truncated). Each continues 4 spaces were converted to a single tab character (`\t`) before tokenization. |
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## Eval results |
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The model achieved 87.66%/87.46% accuracy on AI-SOCO task and ranked in the 9th place. |
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### BibTeX entry and citation info |
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```bibtex |
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@inproceedings{ai-soco-2020-fire, |
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title = "Overview of the {PAN@FIRE} 2020 Task on {Authorship Identification of SOurce COde (AI-SOCO)}", |
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author = "Fadel, Ali and Musleh, Husam and Tuffaha, Ibraheem and Al-Ayyoub, Mahmoud and Jararweh, Yaser and Benkhelifa, Elhadj and Rosso, Paolo", |
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booktitle = "Proceedings of The 12th meeting of the Forum for Information Retrieval Evaluation (FIRE 2020)", |
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year = "2020" |
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} |
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``` |
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<a href="https://huggingface.co/exbert/?model=aliosm/ai-soco-c++-roberta-tiny-clas"> |
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<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png"> |
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</a> |
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