---
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small ar1 - Mohamed Shaaban
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common standard ar Voice 11.0
      type: mozilla-foundation/common_voice_11_0
    metrics:
    - name: Wer
      type: wer
      value: 65.27199999999999
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small ar1 - Mohamed Shaaban

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common standard ar Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4585
- Wer: 65.2720

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.444         | 0.42  | 1000 | 0.5684          | 73.7587 |
| 0.4161        | 0.83  | 2000 | 0.4995          | 68.0147 |
| 0.3282        | 1.25  | 3000 | 0.4841          | 68.92   |
| 0.2915        | 1.66  | 4000 | 0.4663          | 67.6120 |
| 0.2639        | 2.08  | 5000 | 0.4585          | 65.2720 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2