Update README.md

README.md

@@ -11,4 +11,38 @@ tags:
 - sentiment-analysis
 - movie-analysis
 - sentiment
----
+- distilbert
+- movie-reviews
+---
+
+## Model Description
+This model is a `distilbert-base-uncased` fine-tuned for sentiment analysis on the IMDb movie review dataset. The model is trained to classify movie reviews into positive or negative sentiment.
+
+## Intended Use
+The model is intended for sentiment analysis tasks, specifically to classify the sentiment of English-language movie reviews. It can be used by developers or data scientists who wish to include sentiment analysis features in their applications.
+
+## Training Data
+The model was fine-tuned on the IMDb movie review dataset available from the Hugging Face datasets library. The dataset consists of 50,000 movie reviews from IMDb, labeled as positive or negative.
+
+## Training Procedure
+The model was fine-tuned for 2 epochs with a batch size of 8, Adam optimizer with a learning rate of 2e-5.
+
+## Ethical Considerations
+This model may inherit biases present in the IMDb dataset, and its predictions should be reviewed with critical consideration, especially if used in sensitive contexts.
+
+## Sample Usage in Python
+Here's how you can use this model in Python:
+
+```python
+from transformers import pipeline
+
+# Load the sentiment analysis pipeline
+classifier = pipeline('sentiment-analysis', model='sarahai/movie-sentiment-analysis')
+
+# Analyze sentiment
+review = "I really enjoyed this movie from start to finish!"
+result = classifier(review)
+
+print(result)
+
+```