---
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 Medium 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: 47.53066666666667
---

<!-- 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 Medium Arabic

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4218
- Wer: 47.5307

## 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: 4
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2215        | 0.1   | 1000  | 0.3361          | 49.9307 |
| 0.1134        | 1.07  | 2000  | 0.3290          | 56.76   |
| 0.0765        | 2.04  | 3000  | 0.3400          | 54.3947 |
| 0.0417        | 3.01  | 4000  | 0.3599          | 52.5320 |
| 0.0364        | 3.11  | 5000  | 0.3740          | 55.5653 |
| 0.0094        | 4.08  | 6000  | 0.4152          | 56.4307 |
| 0.0077        | 5.05  | 7000  | 0.4218          | 47.5307 |
| 0.0018        | 6.02  | 8000  | 0.4556          | 50.0493 |
| 0.0012        | 6.12  | 9000  | 0.4760          | 54.8147 |
| 0.0009        | 7.09  | 10000 | 0.4711          | 48.7533 |


### Framework versions

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