Update README.md

README.md

@@ -37,10 +37,12 @@ The models are fine-tuned with the MathInstruct dataset using the original Llama
 The models are evaluated using open-ended and multiple-choice math problems from several datasets. Here are the results:
 
 
-| **Model**             	| **Decoding** 	| **GSM**  	| **MATH** 	| **AQuA** 	| **NumG** 	| **SVA**  	| **Mat**  	| **Sim**  	| **SAT**  	| **MMLU** 	| **AVG**  	|
-|---------------------------|---------------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|
-| **MAmmoTH-7B-Mistral**    | CoT          	| 50.5     	| 10.4     	| 43.7     	| 44.0     	| 47.3     	| 9.2      	| 18.9     	| 32.7     	| 39.9     	| 33.0     	|
-|                       	| PoT          	| 51.6     	| 28.7     	| 43.3     	| 52.3     	| 65.1     	| 41.9     	| 48.2     	| 39.1     	| 44.6     	| 46.1     	|
+| **Model**             	| **Decoding** 	| **GSM**  	| **MATH** 	| **MMLU** 	|
+|---------------------------|---------------|-----------|-----------|-----------|
+| **MAmmoTH-7B-Mistral**    | CoT          	|        	|        	|           |
+|                       	| PoT          	|        	|        	|           |
+|                       	| Hybrid        | 75.0     	| 40.0     	|           |
+
 
 ## Usage
 You can use the models through Huggingface's Transformers library. Use the pipeline function to create a text-generation pipeline with the model of your choice, then feed in a math problem to get the solution.