---
language:
- ara
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- AsemBadr/GP
metrics:
- wer
model-index:
- name: Whisper Small for Quran Recognition
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Quran_Reciters
      type: AsemBadr/GP
      config: default
      split: test
      args: 'config: default, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 3.2834794567646557
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Small for Quran Recognition

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Quran_Reciters dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0210
- Wer: 3.2835

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0073        | 1.62  | 500   | 0.0249          | 5.0026 |
| 0.0014        | 3.24  | 1000  | 0.0214          | 4.1086 |
| 0.0008        | 4.85  | 1500  | 0.0221          | 3.9883 |
| 0.0           | 6.47  | 2000  | 0.0180          | 2.9740 |
| 0.0           | 8.09  | 2500  | 0.0177          | 3.0944 |
| 0.0           | 9.71  | 3000  | 0.0178          | 3.0944 |
| 0.0           | 11.33 | 3500  | 0.0179          | 3.1288 |
| 0.0           | 12.94 | 4000  | 0.0179          | 3.1288 |
| 0.0           | 14.56 | 4500  | 0.0181          | 2.8881 |
| 0.0           | 16.18 | 5000  | 0.0184          | 2.9225 |
| 0.0           | 17.8  | 5500  | 0.0186          | 3.0256 |
| 0.0           | 19.42 | 6000  | 0.0188          | 3.1803 |
| 0.0           | 21.04 | 6500  | 0.0190          | 3.1631 |
| 0.0           | 22.65 | 7000  | 0.0191          | 3.1631 |
| 0.0           | 24.27 | 7500  | 0.0192          | 3.1803 |
| 0.0           | 25.89 | 8000  | 0.0192          | 3.1631 |
| 0.0           | 27.51 | 8500  | 0.0196          | 3.2491 |
| 0.0           | 29.13 | 9000  | 0.0199          | 3.2491 |
| 0.0           | 30.74 | 9500  | 0.0202          | 3.2835 |
| 0.0           | 32.36 | 10000 | 0.0204          | 3.2319 |
| 0.0           | 33.98 | 10500 | 0.0207          | 3.2835 |
| 0.0           | 35.6  | 11000 | 0.0209          | 3.2663 |
| 0.0           | 37.22 | 11500 | 0.0210          | 3.2835 |
| 0.0           | 38.83 | 12000 | 0.0210          | 3.2835 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.1