distilbert-base-uncased__sst2__train-8-3 Open Source Model - Free Deployment to Boost Text Classification Tasks

Distilbert Base Uncased Sst2 Train 8 3

Developed by SetFit

This model is a fine-tuned version of distilbert-base-uncased on the SST-2 dataset, primarily used for text classification tasks.

Text Classification

Transformers

Open Source License:Apache-2.0 #Sentiment Analysis #Text Classification #Low-resource Optimization

Downloads 25

Release Time : 3/2/2022

Model Overview

This is a fine-tuned DistilBERT model suitable for sentiment analysis tasks, specifically trained on the SST-2 dataset.

Model Features

Lightweight Model

Based on the DistilBERT architecture, it is smaller and faster than the standard BERT model while maintaining good performance.

Sentiment Analysis

Fine-tuned specifically for sentiment analysis tasks, suitable for text sentiment classification.

Model Capabilities

Text Classification

Sentiment Analysis

Use Cases

Sentiment Analysis

Product Review Sentiment Analysis

Analyze whether user reviews of a product are positive or negative.

Social Media Sentiment Monitoring

Monitor user sentiment trends on social media.

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6931	1.0	3	0.7039	0.25
0.6615	2.0	6	0.7186	0.25
0.653	3.0	9	0.7334	0.25
0.601	4.0	12	0.7592	0.25
0.5555	5.0	15	0.7922	0.25
0.4832	6.0	18	0.8179	0.25
0.4565	7.0	21	0.8285	0.25
0.3996	8.0	24	0.8559	0.25
0.3681	9.0	27	0.8586	0.5
0.2901	10.0	30	0.8646	0.5
0.241	11.0	33	0.8524	0.5

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Distilbert Base Uncased Sst2 Train 8 3

Model Overview

Model Features

Model Capabilities

Use Cases