Update README.md

README.md

@@ -1,3 +1,56 @@
 ---
 license: mit
+datasets:
+- mwz/ur_para
+language:
+- ur
+tags:
+- 'paraphrase '
 ---
+# Urdu Paraphrasing Model
+
+This repository contains a pretrained model for Urdu paraphrasing. The model is based on the BERT architecture and has been fine-tuned on a large dataset of Urdu paraphrases.
+
+## Model Description
+
+The pretrained model is based on the BERT architecture, specifically designed for paraphrasing tasks in the Urdu language. It has been trained using a large corpus of Urdu text to generate high-quality paraphrases.
+
+## Model Details
+
+- Model Name: Urdu-Paraphrasing-BERT
+- Base Model: BERT
+- Architecture: Transformer
+- Language: Urdu
+- Dataset: Urdu Paraphrasing Dataset mwz/ur_para
+
+## How to Use
+
+You can use this pretrained model for generating paraphrases for Urdu text. Here's an example of how to use the model:
+
+```python
+from transformers import pipeline
+
+# Load the model
+model = pipeline("text2text-generation", model="path_to_pretrained_model")
+
+# Generate paraphrases
+input_text = "Urdu input text for paraphrasing."
+paraphrases = model(input_text, max_length=128, num_return_sequences=3)
+
+# Print the generated paraphrases
+print("Original Input Text:", input_text)
+print("Generated Paraphrases:")
+for paraphrase in paraphrases:
+    print(paraphrase["generated_text"])
+```
+## Training
+The model was trained using the Hugging Face transformers library. The training process involved fine-tuning the base BERT model on the Urdu Paraphrasing Dataset.
+
+## Evaluation
+The model's performance was evaluated on a separate validation set using metrics such as BLEU, ROUGE, and perplexity. However, please note that the evaluation results may vary depending on the specific use case.
+
+## Acknowledgments
+- The pretrained model is based on the BERT architecture developed by Google Research.
+
+## License
+This model and the associated code are licensed under the MIT License.