---
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: 0.0060
- Wer: 0.0688
- Cer: 0.0280

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0058        | 1.0     | 157  | 0.0056          | 0.0608 | 0.0253 |
| 0.0052        | 2.0     | 314  | 0.0055          | 0.0583 | 0.0240 |
| 0.0037        | 3.0     | 471  | 0.0054          | 0.0586 | 0.0247 |
| 0.0032        | 4.0     | 628  | 0.0054          | 0.0615 | 0.0242 |
| 0.0038        | 5.0     | 785  | 0.0056          | 0.0581 | 0.0235 |
| 0.0015        | 6.0     | 942  | 0.0058          | 0.0610 | 0.0245 |
| 0.0023        | 7.0     | 1099 | 0.0062          | 0.0612 | 0.0245 |
| 0.0014        | 8.0     | 1256 | 0.0066          | 0.0639 | 0.0251 |
| 0.0013        | 9.0     | 1413 | 0.0070          | 0.0693 | 0.0361 |
| 0.0007        | 10.0    | 1570 | 0.0074          | 0.0671 | 0.0349 |
| 0.0006        | 11.0    | 1727 | 0.0078          | 0.0695 | 0.0363 |
| 0.0002        | 12.0    | 1884 | 0.0082          | 0.0733 | 0.0387 |
| 0.0001        | 13.0    | 2041 | 0.0084          | 0.0710 | 0.0374 |
| 0.0001        | 14.0    | 2198 | 0.0086          | 0.0688 | 0.0452 |
| 0.0002        | 15.0    | 2355 | 0.0088          | 0.0706 | 0.0454 |
| 0.0001        | 16.0    | 2512 | 0.0089          | 0.0717 | 0.0455 |
| 0.0001        | 17.0    | 2669 | 0.0090          | 0.0711 | 0.0455 |
| 0.0001        | 18.0    | 2826 | 0.0090          | 0.0711 | 0.0361 |
| 0.0           | 19.0    | 2983 | 0.0098          | 0.0870 | 0.0457 |
| 0.0001        | 19.8768 | 3120 | 0.0091          | 0.0706 | 0.0362 |


### Framework versions

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