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Distilroberta Base
DistilRoBERTa is a lightweight distilled version of the RoBERTa model, retaining most of its performance while being smaller and faster.
Downloads 37
Release Time : 3/2/2022
Model Overview
This model is a distilled version of RoBERTa, reducing model size through knowledge distillation while maintaining most of the original model's performance. Suitable for various natural language processing tasks.
Model Features
Lightweight and Efficient
Through knowledge distillation, the model size is reduced by 40% and speed is increased by 60%, while retaining 97% of the performance.
Versatility
Suitable for various natural language processing tasks, including text classification and named entity recognition.
Easy Deployment
Smaller model size makes it more suitable for production environment deployment.
Model Capabilities
Text classification
Named entity recognition
Question answering systems
Text similarity calculation
Sentiment analysis
Use Cases
Text Analysis
Sentiment Analysis
Analyze sentiment tendencies in social media text
Can accurately identify positive, negative, and neutral sentiments
Content Classification
Classify news articles
Achieves classification accuracy close to that of the full RoBERTa model
Information Extraction
Named Entity Recognition
Extract entities such as person names, locations, and organizations from text
Performs well on standard datasets
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