Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+  - text-classification
+  - emotion-detection
+  - bert
+  - huggingface
+language:
+  - en
+pipeline_tag: text-classification
+---
+
+# BERT-based Emotion Classification Model 🎭
+
+This model is a fine-tuned version of BERT for **emotion classification**. It predicts one of six emotion categories from a given English text input.
+
+## 🧠 Model Details
+
+- **Architecture**: `BertForSequenceClassification`
+- **Base Model**: `bert-base-uncased`
+- **Labels**:
+  - `0`: sadness
+  - `1`: joy
+  - `2`: love
+  - `3`: anger
+  - `4`: fear
+  - `5`: surprise
+- **Problem Type**: Single-label classification
+- **Hidden Size**: 768
+- **Max Sequence Length**: 512
+- **Number of Layers**: 12
+
+## 🚀 How to Use
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("text-classification", model="AbhishekBhavnani/TweetClassification")
+result = classifier("I'm feeling so happy today!")
+print(result)
+```
+
+##  Example 
+
+**Input**:
+```text
+I can't stop smiling, this movie is too funny!
+```
+
+**Input**: 
+```text
+[{'label': 'joy', 'score': 0.9821}]
+```