Update README.md

Added Interpretation

README.md

@@ -28,7 +28,8 @@ Utilizing this approach, we demonstrated improvements in regression tasks for ev
 # main
 
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/654e897ddd2482b0592bfffa/cptDT8s2FueH89mK9Bz4S.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/654e897ddd2482b0592bfffa/EqqRYWJKBFY96cy2v_QPD.png)
 
 # augmented
 
@@ -46,6 +47,22 @@ Utilizing this approach, we demonstrated improvements in regression tasks for ev
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/654e897ddd2482b0592bfffa/dR9oN4kFbPsnimJVV2ePe.png)
 
+# Interpretation
+
+We can only compare our classification task with the BART model that has the highest classification. This model only classifies whether the value is present or not.
+1 for present and 0 for not. Qiu et al (2022) used BART to perform this classification with the highest accuracy using the main dataset with 67%. Using DeBERTa v3,
+we were able to get an accuracy of 73% (0.7283). DeBERTa's disentanglement feature allows for a significant improvement in classifying human values.
+
+We can also see a very noticable improvement with the regression tasks. This is a more difficult task, because the model must determine if the value in question is either
+present or not; then determine if the agent's perspective is either supporting or against the value's stance. However, we can see that DeBerta v3 outperforms BERT by 4% (65% vs 61%).
+I simply just replicated Qiu et al (2022) and have not tried to improve their design.
+
+# Future Work
+
+I am currently working to develop and ensemble model that will leverage text generation to create multiple stance positions for each values. We hypothesize that if
+the model can differentiate between different stance positions on the same topic associated with the target value, the model can more accurately predict an agents
+values stance.
+
 ## Acknowledgements
 
 We would like to acknowledge the authors of the ValueNet dataset for their valuable contribution to this work.