readme: ---
  ---
  language: ar
  widget:
   - text: "قفا نبك من ذِكرى حبيب ومنزلِ  بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ"
   - text: "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتابا"
  co2_eq_emissions: 404.66986451902227
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - CO2 Emissions (in grams): 404.66986451902227
  ## Dataset
  We used the APCD dataset cited hereafter for pretraining the model. The dataset has been cleaned and only the main text and the meter columns 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: 0.21315555274486542
  - Accuracy: 0.9493554089595999
  - Macro F1: 0.7537353091512587
  
  ## 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": "قفا نبك من ذِكرى حبيب ومنزلِ  بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ"}' https://api-inference.huggingface.co/models/Yah216/Arabic_poem_meter_3
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Yah216/Arabic_poem_meter_3", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Yah216/Arabic_poem_meter_3", use_auth_token=True)
  
  inputs = tokenizer("قفا نبك من ذِكرى حبيب ومنزلِ  بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ", return_tensors="pt")
  
  outputs = model(**inputs)
  ```