Update README.md

README.md

@@ -42,8 +42,8 @@ You can use this model directly with a simple API call in Hugging Face. Here is
 ```python
 from transformers import AutoModelForCTC, Wav2Vec2Processor
 
-model = AutoModelForCTC.from_pretrained("your-username/your-model-name")
-processor = Wav2Vec2Processor.from_pretrained("your-username/your-model-name")
+model = AutoModelForCTC.from_pretrained("rukaiyah-indika-ai/whisper-medium-hindi-fine-tuned")
+processor = Wav2Vec2Processor.from_pretrained("rukaiyah-indika-ai/whisper-medium-hindi-fine-tuned")
 
 # Replace 'path_to_audio_file' with the path to your Hindi audio file
 input_audio = processor(path_to_audio_file, return_tensors="pt", padding=True)
@@ -59,17 +59,17 @@ enhancing the accuracy by 2-5% for each language. The word error rate has also b
 
 The additional languages include:
 
-| Language     | Accuracy Improvement | Word Error Rate Reduction                            | 
-|--------------|----------------------|------------------------------------------------------|
-| Bengali      | +3.5%                | -18%                                                 | 
-| Telugu       | +2.8%                | -15%                                                 |
-| Marathi      | +4.2%                | -20%                                                 | 
-| Tamil        | +3.0%                | -17%                                                 |
-| Gujarati     | +2.2%                | -12%                                                 | 
-| Kannada      | +4.5%                | -21%                                                 | 
-| Malayalam    | +3.8%                | -19%                                                 | 
-| Punjabi      | +2.0%                | -11%                                                 |
-| Odia         | +4.0%                | -20%                                                 | 
+| Language   | Original Accuracy | Accuracy Improvement | Word Error Rate Reduction|
+|------------|-------------------|----------------------|--------------------------|
+| Bengali    | 88%               | +3.5%                | -18%                     |
+| Telugu     | 86%               | +2.8%                | -15%                     |
+| Marathi    | 87%               | +4.2%                | -20%                     |
+| Tamil      | 85%               | +3.0%                | -17%                     |
+| Gujarati   | 84%               | +2.2%                | -12%                     |
+| Kannada    | 86.5%             | +4.5%                | -21%                     |
+| Malayalam  | 87.5%             | +3.8%                | -19%                     |
+| Punjabi    | 83%               | +2.0%                | -11%                     |
+| Odia       | 88.5%             | +4.0%                | -20%                     |
 
 
 ### BibTeX entry and citation info