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ABSA MaskedLM BERTbase Finetuned Sentihood
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ABSA MaskedLM BERTbase Finetuned Sentihood

Developed by UchihaMadara
A model fine-tuned based on bert-base-uncased for aspect-based sentiment analysis tasks
Large Language Model
Transformers
Open Source License:Apache-2.0#Aspect-based sentiment analysis#BERT fine-tuning#Fine-grained classification
Downloads 25
Release Time : 1/4/2023

Model Overview

This model is a fine-tuned Aspect-Based Sentiment Analysis (ABSA) model based on the BERT-base architecture, specifically optimized for the sentihood dataset, capable of identifying sentiment tendencies towards specific aspects in text.

Model Features

Aspect-Based Sentiment Analysis
Capable of identifying sentiment tendencies towards specific aspects (such as location, service, etc.) in text
BERT-base Fine-tuning
Domain-adaptive fine-tuning based on the powerful BERT-base architecture
Efficient Training
Achieves good results with just 3 training epochs

Model Capabilities

Text sentiment analysis
Aspect-based sentiment recognition
Natural language understanding

Use Cases

Sentiment Analysis
Location Evaluation Analysis
Analyze sentiment tendencies towards specific locations in user reviews
Validation loss 0.0968
Service Feedback Analysis
Extract sentiments towards specific service aspects from customer feedback
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