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---
language: en
license: mit
library_name: transformers
tags:
- summarization
- bart
datasets: ccdv/arxiv-summarization
model-index:
- name: arxiv-accelerate
  results:
  - task:
      type: summarization
    dataset:
      name: Summarization (arXiv)
      type: ccdv/arxiv-summarization
      split: validation
    metrics:
    - type: rouge
      value: 14.842964392434455
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->

#  Table of Contents

1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training Details](#training-details)
5. [Evaluation](#evaluation)
6. [Model Examination](#model-examination-optional)
7. [Environmental Impact](#environmental-impact)
8. [Technical Specifications](#technical-specifications-optional)
9. [Citation](#citation-optional)
10. [Glossary](#glossary-optional)
11. [More Information](#more-information-optional)
12. [Model Card Authors](#model-card-authors-optional)
13. [Model Card Contact](#model-card-contact)
14. [How To Get Started With the Model](#how-to-get-started-with-the-model)


# Model Details

## Model Description

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- **Developed by:** [More Information Needed]
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- **Model type:** [More Information Needed]
- **Language(s) (NLP):** en
- **License:** mit
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# Uses

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## Direct Use

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## Downstream Use [optional]

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## Out-of-Scope Use

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# Bias, Risks, and Limitations

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## Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

# Training Details

## Training Data

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## Training Procedure [optional]

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### Preprocessing

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### Speeds, Sizes, Times

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# Evaluation

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## Testing Data, Factors & Metrics

### Testing Data

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### Factors

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### Metrics

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## Results

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# Model Examination [optional]

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# Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]

# Technical Specifications [optional]

## Model Architecture and Objective

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# Citation [optional]

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**APA:**

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# Glossary [optional]

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# More Information [optional]

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# Model Card Authors [optional]

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# Model Card Contact

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# How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

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</details>