bertweet-sentiment-model

Model Description

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Finetuned BERTweet against neologisms dataset.

• Developed by: Hima Varshini Parasa
• Finetuned from model [optional]: vinai/bertweet-base

Uses

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Useful for sentimental analysis of complex sentences, formed through newly coined words/slangs/informal language - neologisms.

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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.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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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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Summary

Model Examination [optional]

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Environmental Impact

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

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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]

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Model Card Contact

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