readme: ---
  language: 
  - ar
  tags:
  - question-paraphrasing
  widget:
  - text: "أعد صياغة: ما عدد حروف اللغة العربية؟"
  metrics:
  - sacrebleu
  - rouge
  - meteor
  
  ---
  
  # Arabic T5v1.1 for question paraphrasing
  
  This is a fine-tuned [arabic-t5-small](https://huggingface.co/flax-community/arabic-t5-small) on the task of question paraphrasing.
  
  A demo of the trained model using HF Spaces can be found [here](https://huggingface.co/spaces/salti/arabic-question-paraphrasing)
  
  ## Training data
  
  The model was fine-tuned using the [Semantic Question Similarity in Arabic](https://www.kaggle.com/c/nsurl-2019-task8/data) data on kaggle.
  
  Only the rows of the dataset where the label is `True` (the two questions have the same meaning) were taken.
  
  The training data was then also mirrored; so if `q1` and `q2` were two questions with the same meaning, then `(q1, q2)` and `(q2, q1)` were both present in the training set. The evaluation set was kept unmirrored of course.
  
  ## Training config
  
  |                 |          |
  | :-------------: | :------: |
  |  `batch size`   |   128    |
  | `dropout rate`  |   0.1    |
  | `learning rate` |  0.001   |
  |  `lr schedule`  | constant |
  | `weight decay`  |   1e-7   |
  |    `epochs`     |    3     |
  
  ## Results
  
  |                   |        |
  | :---------------: | :----: |
  |  `training loss`  | 0.7086 |
  | `evaluation loss` | 0.9819 |
  |     `meteor`      | 49.277 |
  |   `sacreBLEU-1`   | 57.088 |
  |   `sacreBLEU-2`   | 39.846 |
  |   `sacreBLEU-3`   | 29.444 |
  |   `sacreBLEU-4`   | 22.601 |
  |  `Rouge F1 max`   | 1.299  |
  