|
--- |
|
language: en |
|
--- |
|
|
|
# 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. |
|
|
|
```bash |
|
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 |
|
Copy code |
|
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) |
|
|
|
|
