README.md

---
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- ubulut/quran-verses
metrics:
- wer
model-index:
- name: Whisper Tiny AR - Quran
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: quran-whisper-dataset
      type: ubulut/quran-verses
      config: default
      split: None
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 190.35250463821893
---

<!-- 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 Tiny AR - Quran

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-whisper-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3458
- Wer: 190.3525

## 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: 16
- 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0001        | 500.0  | 1000 | 1.3154          | 243.7848 |
| 0.0001        | 1000.0 | 2000 | 1.3080          | 204.8237 |
| 0.0           | 1500.0 | 3000 | 1.3405          | 221.1503 |
| 0.0           | 2000.0 | 4000 | 1.3458          | 190.3525 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1