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---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- fine-tuned
- Quran
- automatic-speech-recognition
- arabic
- whisper
datasets:
- fawzanaramam/the-truth-1st-chapter
metrics:
- wer
model-index:
- name: Whisper Small Finetuned on Surah Fatiha
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: The Truth 2.0 - Surah Fatiha
type: fawzanaramam/the-truth-1st-chapter
args: 'config: ar, split: train'
metrics:
- name: Word Error Rate (WER)
type: wer
value: 0.0
---
# Whisper Small Finetuned on Surah Fatiha
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small), transcribing Surah Fatiha, the first chapter of the Quran. It has been trained using *The Truth 2.0 - Surah Fatiha* dataset and achieves excellent results with a Word Error Rate (WER) of **0.0**, indicating perfect transcription on the evaluation set.
## Model Description
Whisper Small is a transformer-based automatic speech recognition (ASR) model developed by OpenAI. By fine-tuning it on the *Surah Fatiha* dataset, this model becomes highly accurate in transcribing Quranic recitation. It is designed to assist in religious, educational, and research-oriented tasks that require precise Quranic transcription.
## Performance Metrics
On the evaluation set, the model achieved:
- **Loss**: 0.0088
- **Word Error Rate (WER)**: 0.0
These metrics showcase the model's exceptional performance and reliability in transcribing Surah Fatiha audio.
## Training Results
The following table summarizes the training process and results:
| **Training Loss** | **Epoch** | **Step** | **Validation Loss** | **WER** |
|:------------------:|:---------:|:--------:|:-------------------:|:----------:|
| No log | 0.5556 | 10 | 1.1057 | 96.2766 |
| No log | 1.1111 | 20 | 0.3582 | 29.7872 |
| 0.6771 | 1.6667 | 30 | 0.1882 | 23.4043 |
| 0.6771 | 2.2222 | 40 | 0.0928 | 25.0 |
| 0.0289 | 2.7778 | 50 | 0.0660 | 34.0426 |
| 0.0289 | 3.3333 | 60 | 0.0484 | 32.9787 |
| 0.0289 | 3.8889 | 70 | 0.0241 | 25.5319 |
| 0.0056 | 4.4444 | 80 | 0.0184 | 28.7234 |
| 0.0056 | 5.0 | 90 | 0.0111 | 0.0 |
| 0.0019 | 5.5556 | 100 | 0.0088 | 0.0 |
## Intended Uses & Limitations
### Intended Uses
- **Speech-to-text transcription** of Quranic recitation for Surah Fatiha.
- Educational tools to assist in learning and practicing Quranic recitation.
- Research and analysis of Quranic audio transcription methods.
### Limitations
- This model is fine-tuned specifically for Surah Fatiha and may not generalize well to other chapters or non-Quranic Arabic audio.
- Variability in audio quality, accents, or recitation styles might affect performance.
- Optimal performance is achieved with high-quality audio inputs.
## Training and Evaluation Data
The model was trained on *The Truth 2.0 - Surah Fatiha* dataset, which comprises high-quality audio recordings of Surah Fatiha and their corresponding transcripts. The dataset was meticulously curated to ensure the accuracy and authenticity of Quranic content.
## Training Procedure
### Training Hyperparameters
The following hyperparameters were used during training:
- **Learning Rate**: 1e-05
- **Training Batch Size**: 16
- **Evaluation Batch Size**: 8
- **Seed**: 42
- **Optimizer**: Adam (betas=(0.9, 0.999), epsilon=1e-08)
- **Learning Rate Scheduler**: Linear
- **Warmup Steps**: 10
- **Training Steps**: 100
- **Mixed Precision Training**: Native AMP
### Framework Versions
- **Transformers**: 4.41.1
- **PyTorch**: 2.2.1+cu121
- **Datasets**: 2.19.1
- **Tokenizers**: 0.19.1 |