Model Card for Model ID
Table of Contents
- Model Details
- Uses
- Bias, Risks, and Limitations
- Training Details
- Evaluation
- Model Examination
- Environmental Impact
- Technical Specifications
- Citation
- Glossary
- More Information
- Model Card Authors
- Model Card Contact
- 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): [More Information Needed]
- License: [More Information Needed]
- Finetuned from model [optional]: [More Information Needed]
- Resources for more information: [More Information Needed]
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).
- 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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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.
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Evaluation results
- WER on google/fleurstest set self-reported16.170
- WER on language-and-voice-lab/samromur_asrtest set self-reported10.220
- WER on language-and-voice-lab/althingi_asrtest set self-reported9.670