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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: Positive, Negative, Neutral
  • 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

### Model Loading

You can easily load the pre-trained model for sentiment analysis using Hugging Face's AutoModelForSequenceClassification.

```bash
from transformers import DistilBertForSequenceClassification, DistilBertTokenizerFast

model_name = "ongaunjie/distilbert-cloths-sentiment"  # Replace with a valid model name from Hugging Face's model hub
tokenizer = DistilBertTokenizerFast.from_pretrained(model_name)
model = DistilBertForSequenceClassification.from_pretrained(model_name)