Update README.md

README.md

@@ -23,7 +23,7 @@ library_name: transformers
 
 **More Stringent Data filtering**: To ensure the quality of the learning data, we not only evaluate the correctness of the final answer but also examine the accuracy of the explanation process in the entire summary. This is achieved through an automated evaluation methods developed internally, which can effectively prevent the model from learning false positives.
 
-**Selection of Training Instructions**: The training instruction data we used was sampled from an internal training dataset, with 6,000 samples mainly covering non-graphic math problems in the K12 scenario. It has no intersection with the training data of the benchmark test set. We made such a data selection because our optimization is mainly for applications in the education field.
+**Selection of Training Instructions**: The training instruction data we used was sampled from an internal training dataset. We made this data selection because our optimization is mainly targeted at applications in the education field. To efficiently verify the effectiveness, the sample size is only 6,000 records, mainly covering non-graphical mathematical problems in K12 scenarios, and there is no overlap with the training data of the benchmark test set. It has been proven that with just a small amount of data, it is possible to transform a general-purpose model into a Chain of Thought model with reasoning capabilities similar to those of o1.
 
 ## Evaluation and Results
 ![alt text](image.png)