| --- |
| language: "c++" |
| tags: |
| - exbert |
| - authorship-identification |
| - fire2020 |
| - pan2020 |
| - ai-soco |
| - classification |
| license: "mit" |
| datasets: |
| - ai-soco |
| metrics: |
| - accuracy |
| --- |
| |
| # ai-soco-c++-roberta-tiny-clas |
|
|
| ## Model description |
|
|
| `ai-soco-c++-roberta-tiny` model fine-tuned on [AI-SOCO](https://sites.google.com/view/ai-soco-2020) task. |
|
|
| #### How to use |
|
|
| You can use the model directly after tokenizing the text using the provided tokenizer with the model files. |
|
|
| #### Limitations and bias |
|
|
| The model is limited to C++ programming language only. |
|
|
| ## Training data |
|
|
| 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. |
|
|
| ## Training procedure |
|
|
| 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. |
|
|
| ## Eval results |
|
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| The model achieved 87.66%/87.46% accuracy on AI-SOCO task and ranked in the 9th place. |
|
|
| ### BibTeX entry and citation info |
|
|
| ```bibtex |
| @inproceedings{ai-soco-2020-fire, |
| title = "Overview of the {PAN@FIRE} 2020 Task on {Authorship Identification of SOurce COde (AI-SOCO)}", |
| author = "Fadel, Ali and Musleh, Husam and Tuffaha, Ibraheem and Al-Ayyoub, Mahmoud and Jararweh, Yaser and Benkhelifa, Elhadj and Rosso, Paolo", |
| booktitle = "Proceedings of The 12th meeting of the Forum for Information Retrieval Evaluation (FIRE 2020)", |
| year = "2020" |
| } |
| ``` |
|
|
| <a href="https://huggingface.co/exbert/?model=aliosm/ai-soco-c++-roberta-tiny-clas"> |
| <img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png"> |
| </a> |
| |
