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Deberta V3 Small Finetuned Sst2
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Deberta V3 Small Finetuned Sst2

Developed by mrm8488
This model is a text classification model fine-tuned on the GLUE SST2 dataset using DeBERTa v3 small, demonstrating excellent performance in sentiment analysis tasks.
Text Classification
Transformers
 EnglishOpen Source License:MIT#High-precision text classification#Sentiment analysis#Fine-tuned model
Downloads 33
Release Time : 3/2/2022

Model Overview

This is a text classification model optimized for sentiment analysis tasks, based on the DeBERTa v3 small architecture, achieving 94.04% accuracy after fine-tuning on the SST2 dataset.

Model Features

High accuracy
Achieves 94.04% accuracy on the SST2 validation set
Comprehensive evaluation metrics
Provides multi-dimensional evaluation results including accuracy, precision, recall, AUC, and F1 score
Lightweight architecture
Based on the DeBERTa v3 small version, balancing performance and efficiency

Model Capabilities

Text classification
Sentiment analysis
Natural language understanding

Use Cases

Sentiment analysis
Movie review sentiment analysis
Analyze the sentiment tendency of movie reviews (positive/negative)
94.04% accuracy
Product review classification
Perform sentiment classification on e-commerce product reviews
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