Add documentation updates

supporting/RAGAS_Service/README.md

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 Made using a dataset of 1000 labeled claims from MVP pipeline.
 
-Roberta model trained on an augmented dataset with LLM generated adversarial examples for low frequency labels.
+# Roberta model 
 
-Flan model trained using raw labelled claims, inherrent natural language ability allows for pattern recognition without the need for fake data.
+Trained on an augmented dataset with LLM generated adversarial examples for low frequency labels.
 
-Regression model trained using the roberta dataset.
+![ROBERTA Diagram](/literature/classifierROBERTA.png)
 
+# Flan model 
+
+Trained using raw labelled claims, inherrent natural language ability allows for pattern recognition without the need for fake data.
+
+![FLAN Diagram](/literature/classifierFLAN.png)
+
+# NN Model
+
+Regression model trained like roberta.
+
+![NN Diagram](/literature/classifierNN.png)
+
+
+# Ensemble 
 Used ensemble model in the final version, with the component models available on Hugging Face. 
 
+
+![Ensemble Diagram](/literature/classifierOverall.png)
+
+
 | Model                                                      | % Correct | % Valid taken forward|Used in ensemble|Link
 |------------------------------------------------------------|-----------|----------------------|----------------|-
 | Original                                                   | 53.22     | 61.72                |