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--- |
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language: ar |
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datasets: |
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- Yah216/Poem_Rawiy_detection |
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co2_eq_emissions: 1.8046766441629636 |
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widget: |
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- "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتاب" |
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--- |
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# Model |
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- Problem type: Multi-class Classification |
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- CO2 Emissions (in grams): 1.8046766441629636 |
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## Dataset |
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We used the APCD dataset cited hereafter for pretraining the model. The dataset has been cleaned and only the main text and the Qafiyah column were kept: |
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``` |
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@Article{Yousef2019LearningMetersArabicEnglish-arxiv, |
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author = {Yousef, Waleed A. and Ibrahime, Omar M. and Madbouly, Taha M. and Mahmoud, |
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Moustafa A.}, |
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title = {Learning Meters of Arabic and English Poems With Recurrent Neural Networks: a Step |
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Forward for Language Understanding and Synthesis}, |
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journal = {arXiv preprint arXiv:1905.05700}, |
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year = 2019, |
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url = {https://github.com/hci-lab/LearningMetersPoems} |
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} |
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``` |
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## Validation Metrics |
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- Loss: 0.398613303899765 |
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- Accuracy: 0.912351981006084 |
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- Macro F1: 0.717311758991278 |
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- Micro F1: 0.912351981006084 |
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- Weighted F1: 0.9110094798809955 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/Yah216/Poem_Rawiy_detection |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("Yah216/Poem_Qafiyah_Detection", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("Yah216/Poem_Qafiyah_Detection", use_auth_token=True) |
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inputs = tokenizer("text, return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
