pytorch bart text2text-generation dataset:IteraTeR_full_sent arxiv:2203.03802 transformers autotrain_compatible
---
datasets:
- IteraTeR_full_sent
---

# IteraTeR BART model
This model was obtained by fine-tuning [facebook/bart-base](https://huggingface.co/facebook/bart-base) on [IteraTeR-full-sent](https://huggingface.co/datasets/wanyu/IteraTeR_full_sent) dataset.

Paper: [Understanding Iterative Revision from Human-Written Text](https://arxiv.org/abs/2203.03802) <br>
Authors: Wanyu Du, Vipul Raheja, Dhruv Kumar, Zae Myung Kim, Melissa Lopez, Dongyeop Kang

## Text Revision Task
Given an edit intention and an original sentence, our model can generate a revised sentence.<br>
The edit intentions are provided by [IteraTeR-full-sent](https://huggingface.co/datasets/wanyu/IteraTeR_full_sent) dataset, which are categorized as follows: 
<table>
  <tr>
    <th>Edit Intention</th>
    <th>Definition</th>
    <th>Example</th>
  </tr>
  <tr>
    <td>clarity</td>
    <td>Make the text more formal, concise, readable and understandable.</td>
    <td>
    Original: It's like a house which anyone can enter in it. <br>
    Revised: It's like a house which anyone can enter.
    </td>
  </tr>
  <tr>
    <td>fluency</td>
    <td>Fix grammatical errors in the text.</td>
    <td>
    Original: In the same year he became the Fellow of the Royal Society. <br>
    Revised: In the same year, he became the Fellow of the Royal Society.
    </td>
  </tr>
  <tr>
    <td>coherence</td>
    <td>Make the text more cohesive, logically linked and consistent as a whole.</td>
    <td>
    Original: Achievements and awards Among his other activities, he founded the Karachi Film Guild and Pakistan Film and TV Academy. <br>
    Revised: Among his other activities, he founded the Karachi Film Guild and Pakistan Film and TV Academy.
    </td>
  </tr>
  <tr>
    <td>style</td>
    <td>Convey the writer’s writing preferences, including emotions, tone, voice, etc..</td>
    <td>
    Original: She was last seen on 2005-10-22. <br>
    Revised: She was last seen on October 22, 2005.
    </td>
  </tr>
</table>

## Usage
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("wanyu/IteraTeR-BART-Revision-Generator")
model = AutoModelForSeq2SeqLM.from_pretrained("wanyu/IteraTeR-BART-Revision-Generator")
before_input = '<fluency> I likes coffee.'
model_input = tokenizer(before_input, return_tensors='pt')
model_outputs = model.generate(**model_input, num_beams=8, max_length=1024)
after_text = tokenizer.batch_decode(model_outputs, skip_special_tokens=True)[0]
```