---
language:
- ara
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- uoseftalaat/GP
metrics:
- wer
model-index:
- name: Whisper Small for quran recognition
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Quran_requiters
      type: uoseftalaat/GP
      config: default
      split: test
      args: 'config: default, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 3.369434416365824
---

<!-- 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_requiters dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0183
- Wer: 3.3694

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0026        | 3.24  | 1000 | 0.0205          | 4.4868 |
| 0.0003        | 6.47  | 2000 | 0.0180          | 3.3522 |
| 0.0003        | 6.49  | 2005 | 0.0180          | 3.3522 |
| 0.0003        | 6.5   | 2010 | 0.0180          | 3.3522 |
| 0.0001        | 9.71  | 3000 | 0.0180          | 3.2663 |
| 0.0           | 12.94 | 4000 | 0.0183          | 3.3694 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.1