Update README.md

README.md

@@ -1,44 +1,25 @@
-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.
+---
+language: en
+---
 
-bash
-Copy code
-pip install transformers
-Model Loading: You can easily load the pre-trained model for sentiment analysis using Hugging Face's AutoModelForSequenceClassification.
+# Women's Clothing Reviews Sentiment Analysis with DistilBERT
 
-python
-Copy code
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
+## Overview
 
-model = AutoModelForSequenceClassification.from_pretrained("your-model-name")
-tokenizer = AutoTokenizer.from_pretrained("your-model-name")
-Inference: Tokenize your text data with the provided tokenizer and use the model for sentiment analysis.
+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.
 
-python
-Copy code
-review = "This dress is amazing, I love it!"
-inputs = tokenizer(review, return_tensors="pt")
-outputs = model(**inputs)
-predicted_class = torch.argmax(outputs.logits)
-Customization: Fine-tune the model on your own dataset by following the provided example or training script.
+## Model Details
 
-Reporting: Analyze reviews and extract insights for your specific use case or business needs.
+- **Model Architecture**: Fine-tuned DistilBERT
+- **Sentiment Categories**: Positive, Negative, Neutral
+- **Input Format**: Text-based clothing reviews
+- **Output Format**: Sentiment category labels
 
-Model Card
-For more details on how to use and cite this model, please refer to the accompanying model card.
+## Usage
 
-Issues and Contributions
-If you encounter any issues or have suggestions for improvements, please feel free to open an issue or contribute to this project.
+### Installation
 
-License
-This model is provided under the MIT License.
+To use this model, you'll need to install the Hugging Face Transformers library and any additional dependencies.
 
+```bash
+pip install transformers