readme: ---
  language: ar
  
  datasets:
  - Yah216/Poem_Rawiy_detection
  co2_eq_emissions: 1.8046766441629636
  widget:
   - "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتاب"
  ---
  
  # Model
  
  - Problem type: Multi-class Classification
  - CO2 Emissions (in grams): 1.8046766441629636
  
  ## Dataset
  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:
  ```
  @Article{Yousef2019LearningMetersArabicEnglish-arxiv,
    author =       {Yousef, Waleed A. and Ibrahime, Omar M. and Madbouly, Taha M. and Mahmoud,
                    Moustafa A.},
    title =        {Learning Meters of Arabic and English Poems With Recurrent Neural Networks: a Step
                    Forward for Language Understanding and Synthesis},
    journal =      {arXiv preprint arXiv:1905.05700},
    year =         2019,
    url =          {https://github.com/hci-lab/LearningMetersPoems}
  }
  ```
  
  ## Validation Metrics
  
  - Loss: 0.398613303899765
  - Accuracy: 0.912351981006084
  - Macro F1: 0.717311758991278
  - Micro F1: 0.912351981006084
  - Weighted F1: 0.9110094798809955
  
  
  ## Usage
  
  You can use cURL to access this model:
  
  ```
  $ 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
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Yah216/Poem_Qafiyah_Detection", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Yah216/Poem_Qafiyah_Detection", use_auth_token=True)
  
  inputs = tokenizer("text, return_tensors="pt")
  
  outputs = model(**inputs)
  ```