---
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: 0.0086
- Wer: 0.0799
- Cer: 0.0319

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0108        | 1.0     | 157  | 0.0129          | 0.0771 | 0.0289 |
| 0.0124        | 2.0     | 314  | 0.0113          | 0.0758 | 0.0293 |
| 0.0083        | 3.0     | 471  | 0.0082          | 0.0767 | 0.0300 |
| 0.0053        | 4.0     | 628  | 0.0078          | 0.0742 | 0.0302 |
| 0.0037        | 5.0     | 785  | 0.0084          | 0.0706 | 0.0282 |
| 0.0019        | 6.0     | 942  | 0.0093          | 0.0719 | 0.0276 |
| 0.0013        | 7.0     | 1099 | 0.0102          | 0.0708 | 0.0289 |
| 0.0005        | 8.0     | 1256 | 0.0109          | 0.0744 | 0.0370 |
| 0.0002        | 9.0     | 1413 | 0.0112          | 0.0744 | 0.0369 |
| 0.0001        | 10.0    | 1570 | 0.0116          | 0.0742 | 0.0371 |
| 0.0           | 11.0    | 1727 | 0.0119          | 0.0728 | 0.0374 |
| 0.0           | 12.0    | 1884 | 0.0122          | 0.0748 | 0.0378 |
| 0.0           | 13.0    | 2041 | 0.0124          | 0.0782 | 0.0377 |
| 0.0           | 14.0    | 2198 | 0.0127          | 0.0762 | 0.0366 |
| 0.0           | 15.0    | 2355 | 0.0130          | 0.0771 | 0.0369 |
| 0.0           | 16.0    | 2512 | 0.0133          | 0.0871 | 0.0357 |
| 0.0           | 17.0    | 2669 | 0.0135          | 0.0863 | 0.0362 |
| 0.0           | 18.0    | 2826 | 0.0137          | 0.0782 | 0.0293 |
| 0.0           | 19.0    | 2983 | 0.0141          | 0.0800 | 0.0310 |
| 0.0           | 19.8768 | 3120 | 0.0138          | 0.0776 | 0.0295 |


### Framework versions

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