BARTxiv / README.md
Justin Du
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metadata
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: arxiv-summarization
          type: ccdv/arxiv-summarization
          split: validation
        metrics:
          - type: rouge1
            value: 40.86787138889241
          - type: rouge2
            value: 13.776447449801472

Model Card for Model ID

Table of Contents

  1. Model Details
  2. Uses
  3. Bias, Risks, and Limitations
  4. Training Details
  5. Evaluation
  6. Model Examination
  7. Environmental Impact
  8. Technical Specifications
  9. Citation
  10. Glossary
  11. More Information
  12. Model Card Authors
  13. Model Card Contact
  14. How To Get Started With the Model

Model Details

Model Description

  • Developed by: [More Information Needed]
  • Shared by [optional]: [More Information Needed]
  • Model type: [More Information Needed]
  • Language(s) (NLP): en
  • License: mit
  • Finetuned from model [optional]: [More Information Needed]
  • Resources for more information: [More Information Needed]

Uses

Direct Use

[More Information Needed]

Downstream Use [optional]

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

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

[More Information Needed]

Training Procedure [optional]

Preprocessing

[More Information Needed]

Speeds, Sizes, Times

[More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Model Examination [optional]

[More Information Needed]

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • 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

[More Information Needed]

Compute Infrastructure

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Hardware

[More Information Needed]

Software

[More Information Needed]

Citation [optional]

BibTeX:

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APA:

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Glossary [optional]

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More Information [optional]

[More Information Needed]

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.

Click to expand

[More Information Needed]