Update README.md

README.md

@@ -11,10 +11,22 @@ pipeline_tag: question-answering
 # RoBERTa-Large-KazQAD for Question Answering
 
 ## Model Description
-nur-dev/roberta-large-kazqad is a fine-tuned version of RoBERTa-Kaz-Large, specifically optimized for the Question Answering (QA) task using the Kazakh Open-Domain Question Answering Dataset (KazQAD). This model is trained to extract precise answers from given contexts in the Kazakh language.
+**RoBERTa-Large-KazQAD** is a fine-tuned version of [RoBERTa-Kaz-Large](https://huggingface.co/nur-dev/roberta-kaz-large), specifically optimized for the Question Answering (QA) task using the Kazakh Open-Domain Question Answering Dataset (KazQAD). This model is trained to extract precise answers from given contexts in the Kazakh language.
 
-## Usage
-The model can be used with the Hugging Face Transformers library:
+### Fine-Tuning Details
+
+This model was fine-tuned on the KazQAD dataset, which is a Kazakh open-domain question-answering dataset. The fine-tuning process involved adjusting the model's weights to enhance its performance in answering questions based on a given text context. The dataset contains questions and passages from a variety of topics relevant to Kazakh culture, history, geography, and more, making this model highly specialized for understanding and answering questions in the Kazakh language.
+
+## Intended Use
+
+This model is designed for open-domain question-answering tasks in the Kazakh language. It can be used to answer factual questions based on the provided context. It is particularly useful for:
+
+- **Kazakh Natural Language Processing (NLP) tasks**: Enhancing applications involving text comprehension, search engines, chatbots, and virtual assistants in the Kazakh language.
+- **Research and Educational Purposes**: Serving as a benchmark or baseline for further research in Kazakh NLP.
+
+### How to Use
+
+You can easily use this model with the Hugging Face `Transformers` library:
 ```python
 from transformers import AutoModelForQuestionAnswering, AutoTokenizer
 import torch