---
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: 0.0408
- Wer: 0.3145
- Cer: 0.1128

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.1136        | 1.0   | 94   | 0.0777          | 5.3133 | 1.8561 |
| 0.0458        | 2.0   | 188  | 0.0478          | 2.6311 | 1.1803 |
| 0.0292        | 3.0   | 282  | 0.0402          | 1.8776 | 0.9786 |
| 0.0239        | 4.0   | 376  | 0.0369          | 0.9783 | 0.4714 |
| 0.0182        | 5.0   | 470  | 0.0368          | 0.6109 | 0.2680 |
| 0.0163        | 6.0   | 564  | 0.0357          | 0.6387 | 0.2671 |
| 0.0132        | 7.0   | 658  | 0.0363          | 0.3701 | 0.1281 |
| 0.01          | 8.0   | 752  | 0.0369          | 0.5068 | 0.1884 |
| 0.0067        | 9.0   | 846  | 0.0392          | 0.3609 | 0.1184 |
| 0.0056        | 10.0  | 940  | 0.0354          | 0.3155 | 0.1000 |
| 0.0041        | 11.0  | 1034 | 0.0382          | 0.3131 | 0.0964 |
| 0.0027        | 12.0  | 1128 | 0.0363          | 0.3419 | 0.1087 |
| 0.0018        | 13.0  | 1222 | 0.0387          | 0.3640 | 0.1111 |
| 0.0015        | 14.0  | 1316 | 0.0388          | 0.3428 | 0.1179 |
| 0.0012        | 15.0  | 1410 | 0.0382          | 0.3730 | 0.1359 |
| 0.0012        | 16.0  | 1504 | 0.0386          | 0.2863 | 0.0933 |
| 0.0007        | 17.0  | 1598 | 0.0387          | 0.3721 | 0.1560 |
| 0.0005        | 18.0  | 1692 | 0.0391          | 0.2780 | 0.0847 |
| 0.0004        | 19.0  | 1786 | 0.0405          | 0.2985 | 0.1114 |
| 0.0003        | 20.0  | 1880 | 0.0409          | 0.3452 | 0.1222 |
| 0.0002        | 21.0  | 1974 | 0.0405          | 0.3475 | 0.1441 |
| 0.0           | 22.0  | 2068 | 0.0413          | 0.2614 | 0.0754 |
| 0.0           | 23.0  | 2162 | 0.0423          | 0.3339 | 0.1156 |
| 0.0           | 24.0  | 2256 | 0.0426          | 0.2676 | 0.0854 |
| 0.0           | 25.0  | 2350 | 0.0442          | 0.3357 | 0.1101 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1