---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny AR - BH
  results: []
---

<!-- 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 - BH

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0191
- Wer: 0.1462
- Cer: 0.0494

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0148        | 1.0   | 250  | 0.0146          | 0.1685 | 0.0520 |
| 0.0109        | 2.0   | 500  | 0.0144          | 0.1765 | 0.0595 |
| 0.0082        | 3.0   | 750  | 0.0152          | 0.1634 | 0.0542 |
| 0.0065        | 4.0   | 1000 | 0.0155          | 0.1593 | 0.0505 |
| 0.0033        | 5.0   | 1250 | 0.0181          | 0.1644 | 0.0571 |
| 0.0025        | 6.0   | 1500 | 0.0182          | 0.1558 | 0.0533 |
| 0.0024        | 7.0   | 1750 | 0.0180          | 0.1544 | 0.0492 |
| 0.0014        | 8.0   | 2000 | 0.0190          | 0.1461 | 0.0508 |
| 0.001         | 9.0   | 2250 | 0.0196          | 0.1430 | 0.0479 |
| 0.0006        | 10.0  | 2500 | 0.0198          | 0.1467 | 0.0497 |
| 0.0005        | 11.0  | 2750 | 0.0198          | 0.1531 | 0.0503 |
| 0.0004        | 12.0  | 3000 | 0.0197          | 0.1446 | 0.0473 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0