---
language:
- ar
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Arabic - Mostafa Khedr
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ar
      split: None
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 38.02222018180149
---

<!-- 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 Arabic - Mostafa Khedr

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2691
- Wer: 38.0222

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2453        | 0.4156 | 1000 | 0.3289          | 42.9602 |
| 0.2326        | 0.8313 | 2000 | 0.2976          | 42.0990 |
| 0.139         | 1.2469 | 3000 | 0.2883          | 41.0376 |
| 0.1081        | 1.6625 | 4000 | 0.2720          | 39.0763 |
| 0.0543        | 2.0781 | 5000 | 0.2691          | 38.0222 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1