README.md

---
language: en
license: apache-2.0
tags:
- whisper
- automatic-speech-recognition
- speech
- audio
datasets:
- your-dataset-name  # Replace with your actual dataset
metrics:
- wer
- cer
model-index:
- name: AfroLogicInsect/whisper-finetuned-float32
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Your Dataset Name  # Replace
      type: your-dataset-type  # Replace
    metrics:
    - name: WER
      type: wer
      value: "your-wer-score"  # Replace with actual score
---

# AfroLogicInsect/whisper-finetuned-float32

Fine-tuned Whisper model (float32 version) for speech recognition

## Model Details

- **Model Type**: Whisper (Fine-tuned)
- **Language**: English
- **Data Type**: float32
- **Use Cases**: Speech-to-text transcription

## Usage

```python
from transformers import WhisperProcessor, WhisperForConditionalGeneration
import librosa

# Load model and processor
processor = WhisperProcessor.from_pretrained("AfroLogicInsect/whisper-finetuned-float32")
model = WhisperForConditionalGeneration.from_pretrained("AfroLogicInsect/whisper-finetuned-float32")

# Load audio
audio, sr = librosa.load("path/to/audio.wav", sr=16000)

# Process
input_features = processor(audio, sampling_rate=16000, return_tensors="pt").input_features

# Generate transcription
with torch.no_grad():
    predicted_ids = model.generate(input_features)
    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]

print(transcription)
```

## Training Details

- **Base Model**: OpenAI Whisper
- **Training Dataset**: [Add your dataset details]
- **Training Parameters**: [Add your training parameters]
- **Evaluation Metrics**: [Add your evaluation results]

## Limitations and Biases

- This model may have biases present in the training data
- Performance may vary on different accents or audio qualities
- Recommended for English speech recognition tasks

## Citation

If you use this model, please cite:

```bibtex
@misc{whisper-finetuned,
  author = {Daniel AMAH},
  title = {Fine-tuned Whisper Model},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/AfroLogicInsect/whisper-finetuned-float32}
}
```