Update README.md

README.md

@@ -1,3 +1,7 @@
+---
+language:
+- ko
+---
 # keval-2-1b
 keval-2-1b is an advanced evaluation model specifically designed to assess Korean language models using a LLM-as-a-judge approach. It is a departure from the traditional method which utilized chatgpt for evaluations. keval leverages the Gemma2-9b architecture, enhanced through SFT (Supervised Fine-Tuning) and DPO (Direct Policy Optimization). This model is trained on the newly developed Ko-bench dataset, inspired by MT-bench, tailored for Korean linguistic nuances.
 
@@ -161,5 +165,4 @@ The `score` column represents the ratio of correctly predicted labels to the tot
 |---:|:-----------|:---------|:--------|---------:|:-----------|:----------|:-----------|----:|:-----------|:----------|:----------|:----------|:----------|:----------|:-----------|
 |  0 | keval-2-9b | 0 (0.0%) | 50.0%   |       22 | 1 (50.0%)  | 1 (50.0%) | 2 (100.0%) |   0 | 2 (100.0%) | 0         | 0         | 1 (50.0%) | 1 (50.0%) | 1 (50.0%) | 2 (100.0%) |
 |  1 | keval-2-3b | 0 (0.0%) | 45.5%   |       22 | 2 (100.0%) | 1 (50.0%) | 0          |   0 | 2 (100.0%) | 1 (50.0%) | 0         | 1 (50.0%) | 1 (50.0%) | 0         | 2 (100.0%) |
-|  2 | keval-2-1b | 0 (0.0%) | 36.4%   |       22 | 0          | 1 (50.0%) | 2 (100.0%) |   0 | 1 (50.0%)  | 0         | 1 (50.0%) | 0         | 0         | 1 (50.0%) | 2 (100.0%) |
-
+|  2 | keval-2-1b | 0 (0.0%) | 36.4%   |       22 | 0          | 1 (50.0%) | 2 (100.0%) |   0 | 1 (50.0%)  | 0         | 1 (50.0%) | 0         | 0         | 1 (50.0%) | 2 (100.0%) |