---
language:
- ar
license: apache-2.0
base_model: tarteel-ai/whisper-base-ar-quran
tags:
- generated_from_trainer
datasets:
- zolfa
metrics:
- wer
model-index:
- name: Whisper-raghadomar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Zolfa Dataset
      type: zolfa
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 10.344827586206897
---

<!-- 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-raghadomar

This model is a fine-tuned version of [tarteel-ai/whisper-base-ar-quran](https://huggingface.co/tarteel-ai/whisper-base-ar-quran) on the Zolfa Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0325
- Wer: 10.3448

## 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: 2
- 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0002        | 1.0     | 21   | 0.0317          | 10.3448 |
| 0.0002        | 2.0     | 42   | 0.0287          | 10.3448 |
| 0.0001        | 3.0     | 63   | 0.0293          | 10.3448 |
| 0.0002        | 4.0     | 84   | 0.0298          | 10.3448 |
| 0.0002        | 5.0     | 105  | 0.0281          | 10.3448 |
| 0.0002        | 6.0     | 126  | 0.0308          | 10.3448 |
| 0.0002        | 7.0     | 147  | 0.0262          | 10.3448 |
| 0.0008        | 8.0     | 168  | 0.0341          | 10.3448 |
| 0.0002        | 9.0     | 189  | 0.0223          | 3.4483  |
| 0.0003        | 10.0    | 210  | 0.0411          | 10.3448 |
| 0.0002        | 11.0    | 231  | 0.0357          | 10.3448 |
| 0.0003        | 12.0    | 252  | 0.0349          | 10.3448 |
| 0.0001        | 13.0    | 273  | 0.0429          | 10.3448 |
| 0.0003        | 14.0    | 294  | 0.0311          | 10.3448 |
| 0.0003        | 15.0    | 315  | 0.0372          | 10.3448 |
| 0.0002        | 16.0    | 336  | 0.0329          | 10.3448 |
| 0.0002        | 17.0    | 357  | 0.0390          | 10.3448 |
| 0.0004        | 18.0    | 378  | 0.0333          | 10.3448 |
| 0.0002        | 19.0    | 399  | 0.0450          | 10.3448 |
| 0.0003        | 20.0    | 420  | 0.0384          | 10.3448 |
| 0.0002        | 21.0    | 441  | 0.0366          | 10.3448 |
| 0.0002        | 22.0    | 462  | 0.0360          | 10.3448 |
| 0.0001        | 23.0    | 483  | 0.0441          | 10.3448 |
| 0.0006        | 23.8095 | 500  | 0.0325          | 10.3448 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1