---
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: 0.0062
- Wer: 0.0707
- Cer: 0.0287

## 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-06
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0056        | 1.0     | 157  | 0.0061          | 0.0646 | 0.0262 |
| 0.0061        | 2.0     | 314  | 0.0060          | 0.0643 | 0.0263 |
| 0.0055        | 3.0     | 471  | 0.0059          | 0.0715 | 0.0321 |
| 0.0047        | 4.0     | 628  | 0.0060          | 0.0661 | 0.0272 |
| 0.0023        | 5.0     | 785  | 0.0061          | 0.0633 | 0.0257 |
| 0.0035        | 6.0     | 942  | 0.0063          | 0.0652 | 0.0267 |
| 0.0029        | 7.0     | 1099 | 0.0067          | 0.0659 | 0.0274 |
| 0.0017        | 8.0     | 1256 | 0.0070          | 0.0652 | 0.0270 |
| 0.0016        | 9.0     | 1413 | 0.0075          | 0.0668 | 0.0269 |
| 0.0009        | 10.0    | 1570 | 0.0079          | 0.0688 | 0.0282 |
| 0.0007        | 11.0    | 1727 | 0.0082          | 0.0708 | 0.0285 |
| 0.0003        | 12.0    | 1884 | 0.0085          | 0.0713 | 0.0375 |
| 0.0005        | 13.0    | 2041 | 0.0087          | 0.0720 | 0.0299 |
| 0.0002        | 14.0    | 2198 | 0.0089          | 0.0735 | 0.0381 |
| 0.0002        | 15.0    | 2355 | 0.0091          | 0.0742 | 0.0396 |
| 0.0003        | 16.0    | 2512 | 0.0092          | 0.0713 | 0.0299 |
| 0.0001        | 17.0    | 2669 | 0.0093          | 0.0711 | 0.0283 |
| 0.0003        | 18.0    | 2826 | 0.0093          | 0.0710 | 0.0281 |
| 0.0002        | 19.0    | 2983 | 0.0098          | 0.0987 | 0.0418 |
| 0.0001        | 19.8768 | 3120 | 0.0094          | 0.0708 | 0.0279 |


### Framework versions

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