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Xlm Roberta Base Finetuned Marc
A text classification model fine-tuned on the Amazon multilingual comment dataset based on xlm-roberta-base
Downloads 9
Release Time : 3/2/2022
Model Overview
This model is a fine-tuned model for sentiment analysis or score prediction of multilingual comment data, suitable for cross-lingual text classification tasks
Model Features
Multilingual support
Based on the XLM-RoBERTa architecture, it has the ability to process multilingual text
Optimization of comment analysis
Fine-tuned on the Amazon multilingual comment dataset, especially suitable for product comment analysis
Lightweight fine-tuning
Only fine-tuned for 2 rounds, adapting to specific tasks while maintaining the generality of the base model
Model Capabilities
Multilingual text classification
Sentiment analysis
Score prediction
Use Cases
E-commerce analysis
Multilingual product comment classification
Conduct sentiment analysis on multilingual product comments on e-commerce platforms such as Amazon
Mean absolute error of the validation set: 0.5310
Cross-lingual comment quality evaluation
Evaluate the quality or usefulness of comments from users in different languages
Market research
Global market sentiment analysis
Analyze the differences in product evaluations among users in different regions
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