---

language: en

tags:

- sentence correction

- text-generation

license: cc-by-nc-sa-4.0

datasets:

- jfleg

---

# Model
This model utilises T5-base sentence correction pre-trained model. It was fine tuned using [JFLEG](https://arxiv.org/abs/1702.04066) dataset and [Happy Transformer framework](https://github.com/EricFillion/happy-transformer). This model was pre-trained for educational purposes only for correction on local caribbean dialect.
.
___


# Re-training/Fine Tuning

The results of fine-tuning resulted in a final accuracy of 90%


# Usage 



```python

from happytransformer import HappyTextToText, TTSettings

pre_trained_model="T5"
model = HappyTextToText(pre_trained_model, "KES/T5-KES")

arguments = TTSettings(num_beams=4, min_length=1)
sentence = "Wat iz your nam"

correction = model.generate_text("grammar: "+sentence, args=arguments)
if(correction.text.find(" .")):
    correction.text=correction.text.replace(" .", ".")

print(correction.text) # Correction: "What is your name?".

```