Update README.md

README.md

@@ -12,7 +12,9 @@ widget:
 
 # Note
 
-BERT based sentiment analysis, finetune based on https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment .The model trained on hotel human review chinese datasets.
+BERT based sentiment analysis, finetune based on https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment .
+
+The model trained on **hotel human review chinese datasets**.
 
 # Usage
 
@@ -35,4 +37,33 @@ print(result)
 print result
 >> [{'label': 'Positive', 'score': 0.989660382270813}]
 """
+```
+
+# Evaluate
+We compared and evaluated the performance of *Our finetune model* and the *original Erlangshen model* on the **hotel human review test dataset**(5429 negative reviews and 1251 positive reviews).
+
+The results showed that our model substantial improved the precision and recall of positive review:
+
+```text
+Our finetune model:
+              precision    recall  f1-score   support
+
+    Negative       0.99      0.98      0.98      5429
+    Positive       0.92      0.95      0.93      1251
+
+    accuracy                           0.97      6680
+   macro avg       0.95      0.96      0.96      6680
+weighted avg       0.97      0.97      0.97      6680
+
+======================================================
+
+Original Erlangshen model:
+              precision    recall  f1-score   support
+
+    Negative       0.81      1.00      0.90      5429
+    Positive       0.00      0.00      0.00      1251
+
+    accuracy                           0.81      6680
+   macro avg       0.41      0.50      0.45      6680
+weighted avg       0.66      0.81      0.73      6680
 ```