README.md

metadata

model-index:
  - name: DavidErikMollberg/whisper-medium-is
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: is_is
          split: test
        metrics:
          - type: wer
            value: 16.17
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: language-and-voice-lab/samromur_asr
          type: language-and-voice-lab/samromur_asr
          config: samromur_asr
          split: test
        metrics:
          - type: wer
            value: 10.22
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: language-and-voice-lab/althingi_asr
          type: language-and-voice-lab/althingi_asr
          config: althingi_asr
          split: test
        metrics:
          - type: wer
            value: 9.67
            name: WER

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

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• Shared by [optional]: [More Information Needed]
• Model type: [More Information Needed]
• Language(s) (NLP): [More Information Needed]
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• Finetuned from model [optional]: [More Information Needed]
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Uses

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

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]

Preprocessing

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Speeds, Sizes, Times

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Evaluation

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

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

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• Hours used: [More Information Needed]
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• Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

BibTeX:

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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.

Click to expand

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