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Women's Clothing Reviews Sentiment Analysis with DistilBERT

Overview

This Hugging Face repository contains a fine-tuned DistilBERT model for sentiment analysis of women's clothing reviews. The model is designed to classify reviews into positive, negative, or neutral sentiment categories, providing valuable insights into customer opinions.

Model Details

Model Architecture: Fine-tuned DistilBERT
Sentiment Categories: Neutral[0], Negative[1], Positive[2]
Input Format: Text-based clothing reviews
Output Format: Sentiment category labels

Usage

Installation

To use this model, you'll need to install the Hugging Face Transformers library and any additional dependencies.

pip install transformers
pip install torch

Usage
You can easily load the pre-trained model for sentiment analysis using Hugging Face's DistilBertForSequenceClassification and DistilBertTokenizerFast.

python
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from transformers import DistilBertForSequenceClassification, DistilBertTokenizerFast
import torch

model_name = "ongaunjie/distilbert-cloths-sentiment" 
tokenizer = DistilBertTokenizerFast.from_pretrained(model_name)
model = DistilBertForSequenceClassification.from_pretrained(model_name)