Update README.md

README.md

@@ -47,7 +47,7 @@ Since the model is trained to use test-time-compute, the evalutations were perfo
 | MMLU         | 81.6%            | -               | 82.0%       |
 | MATH         | 64.2%            | 69.4%           | 70.2%       |
 | MMLU-Pro     | 65.6%            | 65.0%           | -           |
-| HumanEval    |             | 88.1%           | 87.2%       |
+| HumanEval    | 61.0%            | 88.1%           | 87.2%       |
 
 The evaluations were performed using a fork of Glaive's `simple-evals` codebase. Many thanks to @winglian for performing the evals. The codebase for evaluations can be found here: https://github.com/winglian/simple-evals