---
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: 0.0100
- Wer: 0.1520
- Cer: 0.0580

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0083        | 1.0     | 313  | 0.0106          | 0.1573 | 0.0532 |
| 0.0075        | 2.0     | 626  | 0.0103          | 0.1544 | 0.0535 |
| 0.0076        | 3.0     | 939  | 0.0097          | 0.1605 | 0.0581 |
| 0.0059        | 4.0     | 1252 | 0.0095          | 0.1582 | 0.0562 |
| 0.0056        | 5.0     | 1565 | 0.0094          | 0.1533 | 0.0623 |
| 0.0064        | 6.0     | 1878 | 0.0094          | 0.1736 | 0.0610 |
| 0.0052        | 7.0     | 2191 | 0.0094          | 0.1560 | 0.0560 |
| 0.0046        | 8.0     | 2504 | 0.0093          | 0.1674 | 0.0567 |
| 0.0036        | 9.0     | 2817 | 0.0096          | 0.1437 | 0.0482 |
| 0.0036        | 10.0    | 3130 | 0.0095          | 0.1522 | 0.0518 |
| 0.0032        | 11.0    | 3443 | 0.0095          | 0.1508 | 0.0520 |
| 0.0023        | 12.0    | 3756 | 0.0096          | 0.1466 | 0.0487 |
| 0.0028        | 13.0    | 4069 | 0.0096          | 0.1426 | 0.0461 |
| 0.0028        | 14.0    | 4382 | 0.0100          | 0.1508 | 0.0582 |
| 0.0023        | 14.9536 | 4680 | 0.0097          | 0.1403 | 0.0455 |


### Framework versions

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