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Language Detection Fine Tuned On Xlm Roberta Base
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Language Detection Fine Tuned On Xlm Roberta Base
Developed by ivanlau
This model is a fine-tuned version of xlm-roberta-base on a general language dataset, designed for text classification tasks, particularly language detection.
Downloads 13.37k
Release Time : 3/2/2022
Model Overview
Based on the xlm-roberta-base architecture, this model is fine-tuned specifically for detecting the language of text, achieving an accuracy of 97.38% on the evaluation set.
Model Features
High Accuracy
Achieved 97.38% accuracy on a general language dataset
Multilingual Support
Based on xlm-roberta-base architecture, supports detection of multiple languages
Efficient Fine-Tuning
Utilizes Adam optimizer and linear learning rate scheduler for efficient training
Model Capabilities
Text Classification
Language Detection
Multilingual Text Processing
Use Cases
Content Management
Multilingual Content Classification
Automatically identifies the language type of user-generated content
Accuracy 97.38%
User Analysis
User Language Preference Analysis
Analyzes the language types used by users to understand their preferences
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