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Tiny Bert Sst2 Distilled
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Tiny Bert Sst2 Distilled

Developed by philschmid
This is a text classification model based on the Tiny BERT architecture, fine-tuned on the GLUE SST-2 dataset for sentiment analysis tasks.
Text Classification
Transformers
Open Source License:Apache-2.0#Sentiment Analysis#Lightweight BERT#Text Classification
Downloads 8,080
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the GLUE dataset, primarily used for text classification tasks, especially sentiment analysis.

Model Features

Lightweight Model
Based on the Tiny BERT architecture, the model is small in size and suitable for resource-constrained environments.
Efficient Fine-tuning
Efficiently fine-tuned on the GLUE SST-2 dataset, focusing on sentiment analysis tasks.
Good Performance
Achieved an accuracy of 83.26% on the evaluation set, performing well for a small model.

Model Capabilities

Text Classification
Sentiment Analysis

Use Cases

Sentiment Analysis
Review Sentiment Classification
Used to analyze the sentiment tendency (positive/negative) of user reviews.
Achieved 83.26% accuracy on the SST-2 dataset
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