Final updation

README.md

@@ -21,7 +21,11 @@ https://huggingface.co/Sajib-006/fake_news_detection_xlmRoberta
     * Used pretrained XLM-Roberta base model.
     * Added classifier layer after bert model
     * For tokenization, i used max length of text as 512(which is max bert can handle)
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+    
+## Result:
+    * Using bert base uncased english model, the accuracy was near 85% (For all samples)
+    * Using XLM Roberta base model, the accuracy was almost 100% ( For only 2k samples)
+    
 ## Limitations:
     * Pretrained XLM Roberta is a heavy model. Training it with the full dataset(44k+ samples) was not possible using google colab free version. So i had to take small sample of 2k size for my experiment.
     * As we can see, there is almost 100% accuracy and F1-score for 2000 dataset, so i haven't tried to find misclassified data.