---
language:
- ar
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium - Arabic language
  results: []
datasets:
- google/fleurs
---

<!-- 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 language

This model is a fine-tuned version of [MohammadJamalaldeen/whisper-medium-with-google-fleurs-ar-4000_steps](https://huggingface.co/MohammadJamalaldeen/whisper-medium-with-google-fleurs-ar-4000_steps) on Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3975
- Wer: 17.5375

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0187        | 3.8   | 1000 | 0.3512          | 19.2    |
| 0.0017        | 7.6   | 2000 | 0.3857          | 18.0625 |
| 0.0002        | 11.41 | 3000 | 0.3894          | 17.5875 |
| 0.0001        | 15.21 | 4000 | 0.3975          | 17.5375 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.7.0
- Tokenizers 0.13.2