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Distilbert Base Uncased Finetuned Clinc
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Distilbert Base Uncased Finetuned Clinc
Developed by msavel-prnt
This model is a text classification model fine-tuned on the clinc_oos dataset based on DistilBERT, primarily used for intent recognition tasks.
Downloads 15
Release Time : 3/2/2022
Model Overview
A lightweight text classification model based on the DistilBERT architecture, specifically optimized for intent recognition tasks, achieving 91.8% accuracy on the clinc_oos dataset.
Model Features
Efficient and Lightweight
Based on the DistilBERT architecture, it is smaller in size and faster in inference compared to the original BERT model.
High Accuracy
Achieves 91.8% accuracy on the clinc_oos intent recognition dataset.
Quick Fine-Tuning
Only 5 training epochs are needed to achieve good performance.
Model Capabilities
Text Classification
Intent Recognition
Natural Language Understanding
Use Cases
Dialogue System
Customer Service Bot Intent Recognition
Identify the intent category of user input.
Accuracy 91.8%
Voice Assistant Command Understanding
Perform intent classification after converting user speech to text.
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