ZeroUniqueness/longt5-transformers-finetuned

Model Card for Model ID

Summarize long context english articles

This modelcard aims to be a base template for new models. It has been generated using this raw template.

Model Details

Model Description

Trained at 16384 context length to summarize articles from arxiv-summarization dataset. Fine tuning was run using QLoRA techniques to limit memory usage while targetting as many layers as possible.

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• Finetuned from model [optional]: [More Information Needed]

Uses

Use for simple article summarization tasks:

summarize:
[article]
summary:
...

Direct Use

TODO

Out-of-Scope Use

Not a regular instruction model. Tasks other than summarizations may not work as expected.

Bias, Risks, and Limitations

TODO

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.

How to Get Started with the Model

TODO

Training Details

Training Data

[More Information Needed]

Training Procedure

In progress

Training Hyperparameters

• Training regime: [More Information Needed]

Evaluation

In progress

Testing Data, Factors & Metrics

Testing Data

Factors

Metrics

Results

Summary

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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