Update README.md

README.md

@@ -25,6 +25,7 @@ model-index:
     - name: Wer
       type: wer
       value: 16.033947800693557
+pipeline_tag: automatic-speech-recognition
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,17 +40,19 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+Whisper Tiny Urdu ASR Model
+This Whisper Tiny model has been fine-tuned on the Common Voice 17 dataset, which includes over 55 hours of Urdu speech data. The model was trained twice to optimize its performance:
 
-## Intended uses & limitations
+First Training: The model was trained on the training set and evaluated on the test set for 20 epochs.
+Second Training: The model was retrained on the combined train and validation sets, with the test set used for validation, also for 20 epochs.
+Despite being the smallest variant in its family, this model achieves state-of-the-art performance for Urdu ASR tasks. It is specifically designed for deployment on small devices, offering an excellent balance between efficiency and accuracy.
 
-More information needed
+Intended Use:
 
-## Training and evaluation data
 
-More information needed
+## Intended uses & limitations
 
-## Training procedure
+This model is particularly suited for applications on edge devices with limited computational resources. Additionally, it can be converted to a FasterWhisper model using the CTranslate2 library, allowing for even faster inference on devices with lower processing power.
 
 ### Training hyperparameters
 
@@ -77,4 +80,4 @@ The following hyperparameters were used during training:
 - Transformers 4.42.3
 - Pytorch 2.1.2
 - Datasets 2.20.0
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1