---
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_Ar500d
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0 Arabic
      type: mozilla-foundation/common_voice_17_0
      config: ar
      split: validation
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 23.472893495603564
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper_Small_Ar500d

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 Arabic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2154
- Wer Ortho: 40.5973
- Wer: 23.4729

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.2544        | 0.6002 | 500  | 0.2154          | 40.5973   | 23.4729 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3