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Fnet Base Finetuned Sst2
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Fnet Base Finetuned Sst2

Developed by gchhablani
A text classification model based on Google's FNet architecture fine-tuned on the SST-2 sentiment analysis dataset
Text Classification EnglishOpen Source License:Apache-2.0#Sentiment Analysis#Efficient Transformer#GLUE Fine-tuning
Downloads 16
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of the original FNet-base model on the GLUE SST2 dataset, specifically designed for sentence-level sentiment classification tasks. Compared to the original FNet-base model, it demonstrates improved performance in sentiment analysis tasks.

Model Features

Efficient Architecture
Utilizes the FNet architecture, which replaces traditional attention mechanisms with Fourier transforms, improving computational efficiency while maintaining good performance
Domain Adaptation
Fine-tuned specifically on the SST-2 sentiment analysis dataset, making it suitable for sentence-level sentiment classification tasks
Lightweight
Based on a base-scale model, ideal for deployment in resource-constrained scenarios

Model Capabilities

English Text Classification
Sentiment Analysis
Sentence-level Semantic Understanding

Use Cases

Sentiment Analysis
Product Review Classification
Analyze the sentiment tendency (positive/negative) of user reviews
Achieved 89.45% accuracy on the SST-2 test set
Social Media Monitoring
Monitor sentiment tendencies in social media content
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