---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small AR
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: ar
      split: None
      args: 'config: ar_de, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 44.396092688480046
---

<!-- 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 Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3517
- Wer: 44.3961

## 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2707        | 0.4119 | 1000 | 0.4188          | 51.3000 |
| 0.2452        | 0.8237 | 2000 | 0.3639          | 46.1863 |
| 0.1613        | 1.2356 | 3000 | 0.3470          | 44.9194 |
| 0.1382        | 1.6474 | 4000 | 0.3398          | 45.0351 |
| 0.1177        | 2.0593 | 5000 | 0.3502          | 44.5154 |
| 0.1206        | 2.4712 | 6000 | 0.3501          | 44.9781 |
| 0.1216        | 2.8830 | 7000 | 0.3423          | 43.5258 |
| 0.072         | 3.2949 | 8000 | 0.3517          | 44.3961 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0