---
language:
- ar
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- ymoslem/MediaSpeech
- UBC-NLP/Casablanca
- mozilla-foundation/common_voice_17_0
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Medium ar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: ymoslem/MediaSpeech
      config: ar
      split: test
      args: ar
    metrics:
    - name: Wer
      type: wer
      value: 15.325045470739346
---
<!-- 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 Medium ar

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4504
- Wer: 15.3250

## 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: 32
- 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: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2423        | 0.2   | 1000 | 2.0205          | 21.3178 |
| 0.0667        | 0.4   | 2000 | 2.3750          | 18.2033 |
| 0.047         | 0.6   | 3000 | 2.4276          | 17.5658 |
| 0.0249        | 0.8   | 4000 | 2.7231          | 16.1576 |
| 0.017         | 1.0   | 5000 | 2.4504          | 15.3250 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

## Citation

```bibtex
@misc{deepdml/whisper-medium-ar-mix-norm,
      title={Fine-tuned Whisper medium ASR model for speech recognition in Arabic},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-medium-ar-mix-norm}},
      year={2025}
    }
```