---
library_name: transformers
language:
- en
- hi
---

# Model Card for Model ID





## Model Details

This fine-tuned 🤗 **Whisper** model is optimized for transcribing feedback calls related to citizen grievances into English text.

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model:** [`openai/whisper-small`](https://huggingface.co/openai/whisper-small)

### Model Sources [optional]

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- **Repository:** [DARPG-2024](https://github.com/sanket-poojary-03/Fine-tuning-Whisper)  
- **Demo:** [WHISPER-SPEECH-TO-TEXT-MODEL-FOR-DARPG](https://huggingface.co/spaces/sanket003/WHISPER-SPEECH-TO-TEXT-MODEL-FOR-DARPG)

## Uses  

This fine-tuned **Whisper** model is designed for transcribing feedback calls related to citizen grievances into English text. It is intended for:  

- **Government agencies**: To analyze and process public feedback efficiently.  
- **Customer service teams**: To transcribe and review calls for insights.  

### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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## Technical Specifications [optional]

### Model Architecture and Objective

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#### Hardware

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#### Software

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## Citation [optional]

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## Glossary [optional]

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## Model Card Authors [optional]

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