Update readme

README.md

@@ -25,16 +25,22 @@ The instruction classification schema is based on prior work in large language m
 # Model evaluation
 Model response quality scores were evaluated with double-blind A/B testing that compared dataset responses against what was generated by ChatGPT (version 3.5 turbo). Our evaluation confirmed that response quality predicted preferences for the dataset response over ChatGPT's:
 
-<center>
-<img src="curating_model_eval.png" width="300"/>
-</center>
+| Model response score      | Win rate over ChatGPT |
+| ----------- | ----------- |
+| 0-0.25      | 0.25       |
+| 0.25-0.5   | 0.28        |
+| 0.5-0.75   | 0.43        |
+| 0.75-1.0  | 0.47        |
 
 # Usage
 The model can accept either a dictionary or list of dicts as input. Each dict needs an ```instruction``` field at a bare minimum (in which case it will simply classify the instruction). If a ```response field``` is included, a response score will be returned. Users can also provide a ```dataset field```, which will only change model predictions if it falls under one of the existing sources we trained on (but can be left blank): dolly, helpful-instructions or open-assistant.
 
 ## Example
-Input: 
+Input:
+<br>
 ```{'instruction': 'What are ways I can stay energized throughout the day?', 'response': 'Drink lots of coffee!'}```
-
+<br>
+<br>
 Model output:
+<br>
 ```{'instruction class': 'brainstorming', 'instruction class confidence': 0.9683452, 'response quality': 0.08076164}```