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

<!-- 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: 0.0205
- 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0008        | 4.7619 | 100  | 0.0066          | 6.8966  |
| 0.0003        | 9.5238 | 200  | 0.0205          | 10.3448 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1