SamLowe/Roberta Base Go Emotions

What it is

This model is designed to classify emotions in text using the Roberta architecture, specifically trained on GoEmotions dataset. It's useful for sentiment analysis and understanding emotional nuances in textual data.

This Roberta-based model offers high accuracy for emotion classification tasks, specifically trained on the GoEmotions dataset, making it a specialized tool for understanding emotional nuances in text.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited language support beyond English

   Trained on the GoEmotions dataset, which is primarily in English; performance may degrade for non-English text

2. 02

   Performance overhead due to model size and complexity

   Roberta architecture is large and resource-intensive, leading to slower inference times compared to simpler models

3. 03

   Dependence on specific Python libraries and versions

   Requires specific versions of PyTorch and Transformers library which may cause compatibility issues with other projects

What it does well

• Trained on GoEmotions dataset for nuanced emotion classification

• Uses Roberta architecture for high accuracy in text classification tasks

• Open-source and freely available under Apache-2.0 license

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.