Update README.md

README.md

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 # bert_squad
 
-<!-- Pretrained model on context-based Question Answering using the SQuAD dataset. This model is fine-tuned from the BERT architecture for extracting answers from passages. -->
+Pretrained model on context-based Question Answering using the SQuAD dataset. This model is fine-tuned from the BERT architecture for extracting answers from passages.
 
 
 
-## Model Details
-
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+bert_squad is a transformer-based model trained for context-based question answering tasks. It leverages the pretrained BERT architecture and adapts it for extracting precise answers given a question and a related context. This model uses the Stanford Question Answering Dataset (SQuAD), available via Hugging Face datasets, for training and fine-tuning.
+
+The model was trained using free computational resources, demonstrating its accessibility for educational and small-scale research purposes.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Developed by: SADAT PARVEJ, RAFIFA BINTE JAHIR
+- **Shared by [optional]: SADAT PARVEJ
+- **Language(s) (NLP): ENGLISH
+- **Finetuned from model [optional]:https://huggingface.co/google-bert/bert-base-uncased
 
 ### Model Sources [optional]