Update README.md with LLM colosseum results

README.md

@@ -20,33 +20,36 @@ They need to be:
 https://github.com/OpenGenerativeAI/llm-colosseum/assets/19614572/ec3f2d4b-66b8-4e51-9897-cdab3b160025
 
 
-![LLM colosseum](multi_agents.png)
-
-
 ### 1 VS 1 X 6 : Mistral 7B vs Mistral 7B
 https://github.com/OpenGenerativeAI/llm-colosseum/assets/19614572/2935455f-a78c-436c-92df-a3c3d853c1d3
 
 
 
-# Explanation
-
-Each player is controlled by an LLM. 
-We send to the LLM a text description of the screen. The LLM decide on the next moves its character will make. The next moves depends on its previous moves, the moves of its opponents, its power and health bars. 
-
-- Agent based
-- Multithreading
-- Real time
-
 ## A new kind of benchmark ? 
 
 Street Fighter III assesses the ability of LLMs to understand their environment and take actions based on a specific context.
 As opposed to RL models, which blindly take actions based on the reward function, LLMs are fully aware of the context and act accordingly.
 
-## Results
+# Results 
 
 Our experimentations (342 fights so far) led to the following leader board. 
 Each LLM has an ELO score based on its results 
 
+## Ranking
+
+
+![Win rate matrix](notebooks/win_rate_matrix.png)
+
+
+# Explanation
+
+Each player is controlled by an LLM. 
+We send to the LLM a text description of the screen. The LLM decide on the next moves its character will make. The next moves depends on its previous moves, the moves of its opponents, its power and health bars. 
+
+- Agent based
+- Multithreading
+- Real time
+
 # Installation
 
 - Follow instructions in https://docs.diambra.ai/#installation
@@ -68,3 +71,9 @@ It will choose the action randomly.
 ## Logging
 
 Change the logging level in the `script.py` file.
+
+
+
+# Credits
+
+Made with ❤️ by the OpenGenerativeAI team @oulianov @Pierre-LouisBJT @Platinn @StanGirard during Mistral Hackathon 2024 in San Francisco