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Albert Base V2 Imdb Calssification
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Albert Base V2 Imdb Calssification

Developed by XSY
A text classification model fine-tuned on the IMDB movie review dataset based on ALBERT-base-v2, used to determine sentiment orientation (positive/negative) of reviews
Text Classification
Transformers
Open Source License:Apache-2.0#IMDB sentiment analysis#High-accuracy text classification#ALBERT fine-tuning
Downloads 17
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version for sentiment analysis (binary classification) on the IMDB movie review dataset, capable of accurately determining whether text sentiment is positive or negative

Model Features

High accuracy
Achieves 93.6% classification accuracy on the IMDB test set
Lightweight model
Based on ALBERT's lightweight architecture with fewer parameters compared to traditional BERT models
Specialized for sentiment analysis
Optimized specifically for movie review sentiment analysis tasks

Model Capabilities

Text classification
Sentiment analysis
English text processing

Use Cases

Movie review analysis
Movie review sentiment analysis
Automatically determines whether a user's movie review is positive or negative
93.6% accuracy
Content moderation
User comment sentiment filtering
Identify and filter negative comment content
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