Update README.md

README.md

@@ -52,7 +52,7 @@ To align the model with user preferences we tested many different techniques: DP
 
 Bielik instruct models have been trained with the use of an original open source framework called [ALLaMo](https://github.com/chrisociepa/allamo) implemented by [Krzysztof Ociepa](https://www.linkedin.com/in/krzysztof-ociepa-44886550/). This framework allows users to train language models with architecture similar to LLaMA and Mistral in fast and efficient way.
 
-Bielik-11B-v2.3-Instruct is a linear merge of the [Bielik-11B-v2.0-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.0-Instruct), [Bielik-11B-v2.1-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.1-Instruct), and [Bielik-11B-v2.2-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.2-Instruct) models, each contributing equally with a weight of 1.0. The merge was performed in float16 precision by [Remigiusz Kinas](https://www.linkedin.com/in/remigiusz-kinas/) using [mergekit](https://github.com/cg123/mergekit).
+Bielik-11B-v2.3-Instruct is a merge of the [Bielik-11B-v2.0-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.0-Instruct), [Bielik-11B-v2.1-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.1-Instruct), and [Bielik-11B-v2.2-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.2-Instruct) models. The merge was performed in float16 precision by [Remigiusz Kinas](https://www.linkedin.com/in/remigiusz-kinas/) using [mergekit](https://github.com/cg123/mergekit).
 
 ### Model description:
 
@@ -316,7 +316,7 @@ This benchmark provides a robust and time-efficient method for assessing LLM per
 | Bielik-11B-v2.0-Instruct      | 72.10   | 40.20        |
 | Mistral-7B-Instruct-v0.2      | 70.00   | 36.20        |
 
-The results show that Bielik-11B-v2.3-Instruct performs well on the MixEval benchmark, achieving a score of ~~74.55~~ on the standard MixEval and ~~45.00~~ on MixEval-Hard. Notably, Bielik-11B-v2.3-Instruct significantly outperforms Mistral-7B-Instruct-v0.2 on both metrics, demonstrating its improved capabilities despite being based on a similar architecture.
+The results show that Bielik-11B-v2.3-Instruct performs well on the MixEval benchmark, achieving a score of 72.95 on the standard MixEval and 43.20 on MixEval-Hard. Notably, Bielik-11B-v2.3-Instruct significantly outperforms Mistral-7B-Instruct-v0.2 on both metrics, demonstrating its improved capabilities despite being based on a similar architecture.
 
 
 ## Limitations and Biases