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--- |
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--- |
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language: ar |
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widget: |
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- text: "قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ" |
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- text: "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتابا" |
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co2_eq_emissions: 404.66986451902227 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Multi-class Classification |
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- CO2 Emissions (in grams): 404.66986451902227 |
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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 meter columns 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: 0.21315555274486542 |
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- Accuracy: 0.9493554089595999 |
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- Macro F1: 0.7537353091512587 |
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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": "قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ"}' https://api-inference.huggingface.co/models/Yah216/Arabic_poem_meter_3 |
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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/Arabic_poem_meter_3", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("Yah216/Arabic_poem_meter_3", use_auth_token=True) |
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inputs = tokenizer("قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
