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---
library_name: transformers
tags:
- headline-generation
- tags-generation
- multilingual
license: cc-by-sa-4.0
datasets:
- faisaltareque/XL-HeadTags
pipeline_tag: text2text-generation
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
This is a Text-to-Text model for generating headlines and tags from news articles.



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->
This model is a Text-to-Text model for generating headlines and tags from news articles. This is a Flan-T5 model finetuned on the **XL-HeadTags** multilingual dataset [(read more)](https://aclanthology.org/2024.findings-acl.771/).  

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- **Model type:** T5
- **Finetuned from model :** [Flan-T5](https://huggingface.co/google/flan-t5-large)

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** [XL-HeadTags](https://github.com/faisaltareque/XL-HeadTags)
- **Paper:** [XL-HeadTags](https://aclanthology.org/2024.findings-acl.771/)
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[More Information Needed]

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### Out-of-Scope Use -->

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## Bias, Risks, and Limitations -->

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## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data -->

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### Training Procedure -->

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<!-- #### Preprocessing [optional]

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<!-- #### Training Hyperparameters

- **Training regime:** [More Information Needed] fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

<!-- #### Speeds, Sizes, Times [optional] -->

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## Evaluation -->

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<!-- ### Testing Data, Factors & Metrics

#### Testing Data -->

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#### Factors -->

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### Results -->

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#### Summary -->



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## Environmental Impact -->

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- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]

### Model Architecture and Objective

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## Citation [optional]

```
@inproceedings{shohan-etal-2024-xl,
    title = "{XL}-{H}ead{T}ags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags",
    author = "Shohan, Faisal  and
      Nayeem, Mir Tafseer  and
      Islam, Samsul  and
      Akash, Abu Ubaida  and
      Joty, Shafiq",
    editor = "Ku, Lun-Wei  and
      Martins, Andre  and
      Srikumar, Vivek",
    booktitle = "Findings of the Association for Computational Linguistics ACL 2024",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand and virtual meeting",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.findings-acl.771",
    pages = "12991--13024"
}
```

## Model Card Authors [optional]

- Faisal Tareque Shohan ([email protected])
- Mir Tafseer Nayeem ([email protected])
- Samsul Islam ([email protected])
- Abu Ubaida Akash ([email protected])
- Shafiq Joty ([email protected])

## Model Card Contact
[Faisal Tareque Shohan](mailto:[email protected])