Update README.md

README.md

@@ -1,3 +1,40 @@
----
-license: apache-2.0
----
+---
+language: en
+tags:
+- emotion-classification
+- text-classification
+- deberta
+license: apache-2.0
+---
+
+# DeBERTa Emotion Classifier
+
+This model classifies text into 5 emotions:
+- 😠 Anger
+- 😨 Fear  
+- 😊 Joy
+- 😢 Sadness
+- 😲 Surprise
+
+## Usage
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+model_name = "Somya26/deberta-emotion-classifier"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+text = "I am so happy today!"
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model(**inputs)
+probs = torch.sigmoid(outputs.logits).squeeze()
+
+emotions = ['anger', 'fear', 'joy', 'sadness', 'surprise']
+for emotion, prob in zip(emotions, probs):
+    print(f"{emotion}: {prob:.2%}")
+```
+
+## Training
+
+Trained on emotion classification dataset using DeBERTa-v3-base.