Update README.md

README.md

@@ -5,8 +5,18 @@ datasets:
 language:
 - kk
 metrics:
-- f1
-- exact_match
+  - name: F1 (Before Training)
+    type: F1 Score
+    value: 17.797
+  - name: Exact Match (Before Training)
+    type: Exact Match
+    value: 7.662
+  - name: F1 (After Training)
+    type: F1 Score
+    value: 67.788
+  - name: Exact Match (After Training)
+    type: Exact Match
+    value: 51.428
 base_model:
 - kz-transformers/kaz-roberta-conversational
 new_version: Kundyzka/kaz-roberta-conversational-informatics
@@ -29,11 +39,15 @@ This model was developed by **Kundyz Maksutova**, PhD Candidate, as part of rese
 - **Library**: `adapter-transformers`
 
 ### Performance:
-The model achieves the following metrics:
-- **F1 Score**: Measures overall accuracy in generating answers.
-- **Exact Match (EM)**: Measures exact match between predicted and ground truth answers.
+The model achieves the following performance metrics, highlighting its improvement after fine-tuning:
+- **Before Training**:
+  - F1 Score: 17.797
+  - Exact Match (EM): 7.662
+- **After Training**:
+  - F1 Score: 67.788
+  - Exact Match (EM): 51.428
 
-These metrics were evaluated on the `Kundyzka/informatics_kaz` dataset, ensuring reliable performance in the domain of computer science.
+These metrics were evaluated on the `Kundyzka/informatics_kaz` dataset, demonstrating a significant improvement in performance and reliability for domain-specific questions.
 
 ### Intended Use:
 This model is designed to handle natural language questions in the Kazakh language. It is particularly well-suited for:
@@ -52,4 +66,4 @@ This model is designed to handle natural language questions in the Kazakh langua
 - `Kazakh`
 - `adapter-transformers`
 
-This model is a contribution to advancing natural language processing for low-resource languages like Kazakh, with a focus on computer science applications. For further details, fine-tuning guidelines, or customization, refer to the model repository.
+This model contributes to advancing natural language processing for low-resource languages like Kazakh, with a focus on computer science applications. For further details, fine-tuning guidelines, or customization, refer to the model repository.