---
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: 0.0096
- Wer: 0.1101
- Cer: 0.0435

## 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: 2
- total_train_batch_size: 32
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0074        | 1.0   | 313  | 0.0085          | 0.1014 | 0.0371 |
| 0.0092        | 2.0   | 626  | 0.0080          | 0.1017 | 0.0360 |
| 0.0038        | 3.0   | 939  | 0.0079          | 0.0961 | 0.0329 |
| 0.0049        | 4.0   | 1252 | 0.0081          | 0.1006 | 0.0366 |
| 0.0029        | 5.0   | 1565 | 0.0090          | 0.1023 | 0.0397 |
| 0.0024        | 6.0   | 1878 | 0.0091          | 0.0909 | 0.0323 |
| 0.0045        | 7.0   | 2191 | 0.0096          | 0.0967 | 0.0360 |
| 0.0023        | 8.0   | 2504 | 0.0102          | 0.0999 | 0.0458 |
| 0.0013        | 9.0   | 2817 | 0.0107          | 0.0956 | 0.0439 |


### Framework versions

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