---
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: 6.896551724137931
      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: 0.0196
- Wer: 6.8966

## 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0084        | 2.8571  | 100  | 0.0224          | 6.8966 |
| 0.0017        | 5.7143  | 200  | 0.0177          | 6.8966 |
| 0.0004        | 8.5714  | 300  | 0.0161          | 6.8966 |
| 0.0001        | 11.4286 | 400  | 0.0187          | 6.8966 |
| 0.0003        | 14.2857 | 500  | 0.0171          | 6.8966 |
| 0.0001        | 17.1429 | 600  | 0.0200          | 6.8966 |
| 0.0001        | 20.0    | 700  | 0.0169          | 6.8966 |
| 0.0002        | 22.8571 | 800  | 0.0187          | 6.8966 |
| 0.0002        | 25.7143 | 900  | 0.0186          | 6.8966 |
| 0.0001        | 28.5714 | 1000 | 0.0196          | 6.8966 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1