transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer ar dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_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_16_0 ar
      type: mozilla-foundation/common_voice_16_0
      config: ar
      split: test
      args: ar
    metrics:
    - name: Wer
      type: wer
      value: 58.90729282066525
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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_16_0 ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4005
- Wer: 58.9073

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3404        | 1.53  | 500  | 0.4606          | 66.6216 |
| 0.2707        | 3.07  | 1000 | 0.4295          | 66.8500 |
| 0.2427        | 4.6   | 1500 | 0.4124          | 61.1662 |
| 0.2131        | 6.13  | 2000 | 0.4056          | 62.3038 |
| 0.2085        | 7.67  | 2500 | 0.4012          | 62.2754 |
| 0.1904        | 9.2   | 3000 | 0.3976          | 59.7341 |
| 0.1836        | 10.74 | 3500 | 0.4005          | 58.9073 |
| 0.1653        | 12.27 | 4000 | 0.3989          | 59.7774 |
| 0.1693        | 13.8  | 4500 | 0.3983          | 59.9462 |
| 0.1616        | 15.34 | 5000 | 0.3984          | 59.8300 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
