Accuracy Report

README.md

@@ -36,7 +36,38 @@ Instead of fine-tuning all parameters, **Low-Rank Adaptation (LoRA)** was applie
 - **Dataset:** https://huggingface.co/datasets/imdb
 - **Repository:** https://huggingface.co/ChetanFernandis/distilbert_cls-lora-IMDB
 
----
+## Evaluation Results
+
+The model was evaluated on a held-out validation subset of the **IMDB dataset** using standard classification metrics.
+
+### Confusion Matrix
+
+- **NEGATIVE → NEGATIVE:** 42  
+- **NEGATIVE → POSITIVE:** 11  
+- **POSITIVE → NEGATIVE:** 7  
+- **POSITIVE → POSITIVE:** 40  
+
+This indicates balanced performance across both sentiment classes.
+
+
+### Classification Report
+
+        precision    recall  f1-score   support
+
+NEGATIVE       0.86      0.79      0.82        53
+POSITIVE       0.78      0.85      0.82        47
+
+accuracy                           0.82       100
+
+### Summary
+
+- **Overall Accuracy:** 82%
+- **Balanced F1-score:** 0.82 for both classes
+- Strong precision for **NEGATIVE** reviews
+- Strong recall for **POSITIVE** reviews
+
+These results demonstrate that **LoRA fine-tuning** achieves competitive sentiment classification performance while training only a small fraction of model parameters.
+
 
 ## Uses