---
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 Large 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: 49.431999999999995
---

<!-- 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 Large Arabic

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0 ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3231
- Wer: 49.4320

## 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: 8
- eval_batch_size: 2
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2472        | 0.1   | 1000  | 0.3719          | 58.9560 |
| 0.2015        | 0.2   | 2000  | 0.3487          | 53.5213 |
| 0.1418        | 1.04  | 3000  | 0.3231          | 49.4320 |
| 0.0921        | 1.14  | 4000  | 0.3284          | 56.1107 |
| 0.0923        | 1.24  | 5000  | 0.3304          | 61.4227 |
| 0.0483        | 2.08  | 6000  | 0.3460          | 55.952  |
| 0.0391        | 2.18  | 7000  | 0.3538          | 51.1067 |
| 0.0228        | 3.02  | 8000  | 0.3493          | 51.82   |
| 0.0206        | 3.12  | 9000  | 0.3729          | 52.4000 |
| 0.018         | 3.22  | 10000 | 0.3676          | 51.296  |


### Framework versions

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