---
language:
- ar
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Arabic
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 ar
      type: mozilla-foundation/common_voice_11_0
      config: ar
      split: test
      args: ar
    metrics:
    - name: Wer
      type: wer
      value: 54.08
---

<!-- 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 Small Arabic

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4948
- Wer: 54.08

## 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: 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1885        | 1.03  | 1000  | 0.3950          | 66.44   |
| 0.0794        | 3.0   | 2000  | 0.3950          | 58.5507 |
| 0.0286        | 4.04  | 3000  | 0.4602          | 63.88   |
| 0.0128        | 6.01  | 4000  | 0.4948          | 54.08   |
| 0.0048        | 7.04  | 5000  | 0.5466          | 57.9867 |
| 0.0029        | 9.01  | 6000  | 0.5710          | 55.4147 |
| 0.0013        | 10.05 | 7000  | 0.5996          | 58.7707 |
| 0.0008        | 12.02 | 8000  | 0.6179          | 54.748  |
| 0.0006        | 13.05 | 9000  | 0.6343          | 56.2613 |
| 0.0003        | 15.02 | 10000 | 0.6388          | 56.228  |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2