Update README.md

README.md

@@ -13,4 +13,36 @@ tags:
 - imdb
 - fine-tuned
 - text-classification
----
+---
+
+# 📊 Sentiment Analysis with Fine-Tuned BERT (IMDB)
+
+This repository contains a fine-tuned BERT model for binary sentiment classification using the IMDB movie reviews dataset. The model classifies reviews as **positive** or **negative**, and is built using Hugging Face Transformers and PyTorch.
+
+## 🚀 Model Performance
+
+| Metric           | Value       |
+|------------------|-------------|
+| Accuracy         | 89.4%       |
+| Validation Loss  | 0.375       |
+| Epochs Trained   | 3           |
+| Inference Speed  | ~434 samples/sec |
+
+## 🧠 Model Details
+
+- **Base Model**: `bert-base-uncased`
+- **Dataset**: IMDB (binary sentiment)
+- **Framework**: Hugging Face Transformers
+- **Fine-Tuning Setup**:
+  - Learning rate: 2e-5
+  - Batch size: 32
+  - Mixed-precision: ✅ (`fp16`)
+  - Early stopping: ❌ (trained for full 3 epochs)
+
+## 🛠️ How to Use
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("text-classification", model="Harsha901/tinybert-imdb-sentiment-analysis-model")
+classifier("This movie was absolutely amazing!")